starting build "4e55edc0-5323-4b46-8cde-55f735736088"

FETCHSOURCE
Fetching storage object: gs://244834212502.cloudbuild-source.googleusercontent.com/d03675ea52086605ed3728a79f2a83a61a57f180-7ddde580-a849-405f-9a01-988a218efb79.tar.gz#1590947397051223
Copying gs://244834212502.cloudbuild-source.googleusercontent.com/d03675ea52086605ed3728a79f2a83a61a57f180-7ddde580-a849-405f-9a01-988a218efb79.tar.gz#1590947397051223...
/ [0 files][    0.0 B/  3.4 KiB]                                                
/ [1 files][  3.4 KiB/  3.4 KiB]                                                
Operation completed over 1 objects/3.4 KiB.                                      
BUILD
Already have image (with digest): gcr.io/cloud-builders/docker
Sending build context to Docker daemon  19.97kB

Step 1/6 : FROM rasa/rasa
latest: Pulling from rasa/rasa
afb6ec6fdc1c: Pulling fs layer
2cf47e503ea9: Pulling fs layer
2244bb424472: Pulling fs layer
9322f0967529: Pulling fs layer
5c48bdad7afa: Pulling fs layer
add4445f092a: Pulling fs layer
3a2824b62deb: Pulling fs layer
948b1169c4e7: Pulling fs layer
d2ad3f16f15f: Pulling fs layer
9322f0967529: Waiting
5c48bdad7afa: Waiting
add4445f092a: Waiting
3a2824b62deb: Waiting
948b1169c4e7: Waiting
d2ad3f16f15f: Waiting
2cf47e503ea9: Verifying Checksum
2cf47e503ea9: Download complete
2244bb424472: Verifying Checksum
2244bb424472: Download complete
afb6ec6fdc1c: Verifying Checksum
afb6ec6fdc1c: Download complete
9322f0967529: Verifying Checksum
9322f0967529: Download complete
5c48bdad7afa: Verifying Checksum
5c48bdad7afa: Download complete
add4445f092a: Verifying Checksum
add4445f092a: Download complete
948b1169c4e7: Verifying Checksum
948b1169c4e7: Download complete
d2ad3f16f15f: Verifying Checksum
d2ad3f16f15f: Download complete
3a2824b62deb: Verifying Checksum
3a2824b62deb: Download complete
afb6ec6fdc1c: Pull complete
2cf47e503ea9: Pull complete
2244bb424472: Pull complete
9322f0967529: Pull complete
5c48bdad7afa: Pull complete
add4445f092a: Pull complete
3a2824b62deb: Pull complete
948b1169c4e7: Pull complete
d2ad3f16f15f: Pull complete
Digest: sha256:feffadff337f7e76667eab67f08eaae1fe7f162c0eb37673fc1fe86feabddf20
Status: Downloaded newer image for rasa/rasa:latest
 ---> e0c78f79aaa8
Step 2/6 : ENV BOT_ENV=production
 ---> Running in 857b99856f8b
Removing intermediate container 857b99856f8b
 ---> fc1452289a0e
Step 3/6 : COPY . /var/www
 ---> 31c1bcdc4f15
Step 4/6 : WORKDIR /var/www
 ---> Running in 57c543a1c925
Removing intermediate container 57c543a1c925
 ---> 7dc0f4380c85
Step 5/6 : RUN rasa train
 ---> Running in 10b1e167f607

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Processed trackers: 100%|██████████| 231/231 [00:00<00:00, 529.19it/s, # actions=126]2020-05-31 18:04:40.893884: E tensorflow/stream_executor/cuda/cuda_driver.cc:351] failed call to cuInit: UNKNOWN ERROR (303)


Epochs:   0%|          | 0/100 [00:00<?, ?it/s]
Epochs:   0%|          | 0/100 [00:00<?, ?it/s, t_loss=4.572, loss=4.504, acc=0.213]
Epochs:   1%|          | 1/100 [00:00<00:16,  5.90it/s, t_loss=4.572, loss=4.504, acc=0.213]
Epochs:   1%|          | 1/100 [00:00<00:16,  5.90it/s, t_loss=11.750, loss=11.682, acc=0.587]
Epochs:   2%|▏         | 2/100 [00:00<00:16,  5.89it/s, t_loss=11.750, loss=11.682, acc=0.587]
Epochs:   2%|▏         | 2/100 [00:00<00:16,  5.89it/s, t_loss=10.467, loss=10.398, acc=0.869]
Epochs:   3%|▎         | 3/100 [00:00<00:16,  5.84it/s, t_loss=10.467, loss=10.398, acc=0.869]
Epochs:   3%|▎         | 3/100 [00:00<00:16,  5.84it/s, t_loss=7.928, loss=7.859, acc=0.962]  
Epochs:   4%|▍         | 4/100 [00:00<00:17,  5.57it/s, t_loss=7.928, loss=7.859, acc=0.962]
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Epochs:   7%|▋         | 7/100 [00:01<00:16,  5.65it/s, t_loss=1.074, loss=1.003, acc=0.993]
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Epochs:   8%|▊         | 8/100 [00:01<00:15,  5.91it/s, t_loss=0.710, loss=0.639, acc=0.986]
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Epochs:   9%|▉         | 9/100 [00:01<00:15,  6.06it/s, t_loss=0.435, loss=0.364, acc=1.000]
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Epochs:  10%|█         | 10/100 [00:01<00:14,  6.28it/s, t_loss=0.489, loss=0.418, acc=1.000]
Epochs:  11%|█         | 11/100 [00:01<00:13,  6.37it/s, t_loss=0.489, loss=0.418, acc=1.000]
Epochs:  11%|█         | 11/100 [00:02<00:13,  6.37it/s, t_loss=0.733, loss=0.662, acc=0.993]
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Epochs:  12%|█▏        | 12/100 [00:02<00:13,  6.47it/s, t_loss=0.919, loss=0.848, acc=0.993]
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Epochs:  13%|█▎        | 13/100 [00:02<00:13,  6.62it/s, t_loss=1.332, loss=1.260, acc=1.000]
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Epochs:  15%|█▌        | 15/100 [00:02<00:12,  7.02it/s, t_loss=0.667, loss=0.595, acc=1.000]
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Epochs:  16%|█▌        | 16/100 [00:02<00:11,  7.06it/s, t_loss=0.412, loss=0.341, acc=1.000]
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Epochs:  17%|█▋        | 17/100 [00:02<00:11,  7.10it/s, t_loss=0.368, loss=0.296, acc=1.000]
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Epochs:  18%|█▊        | 18/100 [00:02<00:11,  7.21it/s, t_loss=0.477, loss=0.405, acc=1.000]
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Epochs:  19%|█▉        | 19/100 [00:03<00:11,  7.26it/s, t_loss=0.138, loss=0.066, acc=1.000]
Epochs:  20%|██        | 20/100 [00:03<00:10,  7.40it/s, t_loss=0.138, loss=0.066, acc=1.000]
Epochs:  20%|██        | 20/100 [00:03<00:10,  7.40it/s, t_loss=0.231, loss=0.159, acc=1.000]
Epochs:  21%|██        | 21/100 [00:03<00:10,  7.51it/s, t_loss=0.231, loss=0.159, acc=1.000]
Epochs:  21%|██        | 21/100 [00:03<00:10,  7.51it/s, t_loss=0.638, loss=0.566, acc=1.000]
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Epochs:  23%|██▎       | 23/100 [00:03<00:10,  7.46it/s, t_loss=0.245, loss=0.173, acc=1.000]
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Epochs:  24%|██▍       | 24/100 [00:03<00:10,  7.41it/s, t_loss=0.901, loss=0.829, acc=1.000]
Epochs:  25%|██▌       | 25/100 [00:03<00:10,  7.43it/s, t_loss=0.901, loss=0.829, acc=1.000]
Epochs:  25%|██▌       | 25/100 [00:03<00:10,  7.43it/s, t_loss=0.326, loss=0.254, acc=1.000]
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Epochs:  26%|██▌       | 26/100 [00:04<00:09,  7.64it/s, t_loss=0.329, loss=0.257, acc=1.000]
Epochs:  27%|██▋       | 27/100 [00:04<00:09,  7.82it/s, t_loss=0.329, loss=0.257, acc=1.000]
Epochs:  27%|██▋       | 27/100 [00:04<00:09,  7.82it/s, t_loss=0.796, loss=0.724, acc=1.000]
Epochs:  28%|██▊       | 28/100 [00:04<00:09,  7.93it/s, t_loss=0.796, loss=0.724, acc=1.000]
Epochs:  28%|██▊       | 28/100 [00:04<00:09,  7.93it/s, t_loss=0.294, loss=0.221, acc=1.000]
Epochs:  29%|██▉       | 29/100 [00:04<00:08,  8.04it/s, t_loss=0.294, loss=0.221, acc=1.000]
Epochs:  29%|██▉       | 29/100 [00:04<00:08,  8.04it/s, t_loss=0.203, loss=0.131, acc=1.000]
Epochs:  30%|███       | 30/100 [00:04<00:08,  8.04it/s, t_loss=0.203, loss=0.131, acc=1.000]
Epochs:  30%|███       | 30/100 [00:04<00:08,  8.04it/s, t_loss=0.137, loss=0.065, acc=1.000]
Epochs:  31%|███       | 31/100 [00:04<00:08,  8.13it/s, t_loss=0.137, loss=0.065, acc=1.000]
Epochs:  31%|███       | 31/100 [00:04<00:08,  8.13it/s, t_loss=0.220, loss=0.147, acc=1.000]
Epochs:  32%|███▏      | 32/100 [00:04<00:08,  8.12it/s, t_loss=0.220, loss=0.147, acc=1.000]
Epochs:  32%|███▏      | 32/100 [00:04<00:08,  8.12it/s, t_loss=0.299, loss=0.227, acc=1.000]
Epochs:  33%|███▎      | 33/100 [00:04<00:08,  8.18it/s, t_loss=0.299, loss=0.227, acc=1.000]
Epochs:  33%|███▎      | 33/100 [00:04<00:08,  8.18it/s, t_loss=0.113, loss=0.040, acc=1.000]
Epochs:  34%|███▍      | 34/100 [00:04<00:08,  8.17it/s, t_loss=0.113, loss=0.040, acc=1.000]
Epochs:  34%|███▍      | 34/100 [00:04<00:08,  8.17it/s, t_loss=0.601, loss=0.529, acc=1.000]
Epochs:  35%|███▌      | 35/100 [00:04<00:07,  8.35it/s, t_loss=0.601, loss=0.529, acc=1.000]
Epochs:  35%|███▌      | 35/100 [00:05<00:07,  8.35it/s, t_loss=0.273, loss=0.200, acc=1.000]
Epochs:  36%|███▌      | 36/100 [00:05<00:07,  8.29it/s, t_loss=0.273, loss=0.200, acc=1.000]
Epochs:  36%|███▌      | 36/100 [00:05<00:07,  8.29it/s, t_loss=0.215, loss=0.143, acc=1.000]
Epochs:  37%|███▋      | 37/100 [00:05<00:07,  8.28it/s, t_loss=0.215, loss=0.143, acc=1.000]
Epochs:  37%|███▋      | 37/100 [00:05<00:07,  8.28it/s, t_loss=0.106, loss=0.033, acc=1.000]
Epochs:  38%|███▊      | 38/100 [00:05<00:07,  8.35it/s, t_loss=0.106, loss=0.033, acc=1.000]
Epochs:  38%|███▊      | 38/100 [00:05<00:07,  8.35it/s, t_loss=0.119, loss=0.047, acc=1.000]
Epochs:  39%|███▉      | 39/100 [00:05<00:07,  8.52it/s, t_loss=0.119, loss=0.047, acc=1.000]
Epochs:  39%|███▉      | 39/100 [00:05<00:07,  8.52it/s, t_loss=0.196, loss=0.123, acc=1.000]
Epochs:  40%|████      | 40/100 [00:05<00:06,  8.59it/s, t_loss=0.196, loss=0.123, acc=1.000]
Epochs:  40%|████      | 40/100 [00:05<00:06,  8.59it/s, t_loss=0.107, loss=0.034, acc=1.000]
Epochs:  41%|████      | 41/100 [00:05<00:06,  8.51it/s, t_loss=0.107, loss=0.034, acc=1.000]
Epochs:  41%|████      | 41/100 [00:05<00:06,  8.51it/s, t_loss=0.097, loss=0.025, acc=1.000]
Epochs:  42%|████▏     | 42/100 [00:05<00:06,  8.32it/s, t_loss=0.097, loss=0.025, acc=1.000]
Epochs:  42%|████▏     | 42/100 [00:05<00:06,  8.32it/s, t_loss=0.222, loss=0.149, acc=1.000]
Epochs:  43%|████▎     | 43/100 [00:05<00:06,  8.53it/s, t_loss=0.222, loss=0.149, acc=1.000]
Epochs:  43%|████▎     | 43/100 [00:06<00:06,  8.53it/s, t_loss=0.178, loss=0.106, acc=1.000]
Epochs:  44%|████▍     | 44/100 [00:06<00:06,  8.68it/s, t_loss=0.178, loss=0.106, acc=1.000]
Epochs:  44%|████▍     | 44/100 [00:06<00:06,  8.68it/s, t_loss=0.131, loss=0.059, acc=1.000]
Epochs:  45%|████▌     | 45/100 [00:06<00:06,  8.80it/s, t_loss=0.131, loss=0.059, acc=1.000]
Epochs:  45%|████▌     | 45/100 [00:06<00:06,  8.80it/s, t_loss=0.095, loss=0.023, acc=1.000]
Epochs:  46%|████▌     | 46/100 [00:06<00:06,  8.91it/s, t_loss=0.095, loss=0.023, acc=1.000]
Epochs:  46%|████▌     | 46/100 [00:06<00:06,  8.91it/s, t_loss=0.131, loss=0.058, acc=1.000]
Epochs:  47%|████▋     | 47/100 [00:06<00:05,  9.13it/s, t_loss=0.131, loss=0.058, acc=1.000]
Epochs:  47%|████▋     | 47/100 [00:06<00:05,  9.13it/s, t_loss=0.112, loss=0.040, acc=1.000]
Epochs:  48%|████▊     | 48/100 [00:06<00:05,  9.23it/s, t_loss=0.112, loss=0.040, acc=1.000]
Epochs:  48%|████▊     | 48/100 [00:06<00:05,  9.23it/s, t_loss=0.116, loss=0.044, acc=1.000]
Epochs:  49%|████▉     | 49/100 [00:06<00:05,  9.35it/s, t_loss=0.116, loss=0.044, acc=1.000]
Epochs:  49%|████▉     | 49/100 [00:06<00:05,  9.35it/s, t_loss=0.095, loss=0.022, acc=1.000]
Epochs:  50%|█████     | 50/100 [00:06<00:05,  9.39it/s, t_loss=0.095, loss=0.022, acc=1.000]
Epochs:  50%|█████     | 50/100 [00:06<00:05,  9.39it/s, t_loss=0.077, loss=0.005, acc=1.000]
Epochs:  51%|█████     | 51/100 [00:06<00:05,  9.49it/s, t_loss=0.077, loss=0.005, acc=1.000]
Epochs:  51%|█████     | 51/100 [00:06<00:05,  9.49it/s, t_loss=0.121, loss=0.048, acc=1.000]
Epochs:  52%|█████▏    | 52/100 [00:06<00:05,  9.51it/s, t_loss=0.121, loss=0.048, acc=1.000]
Epochs:  52%|█████▏    | 52/100 [00:06<00:05,  9.51it/s, t_loss=0.174, loss=0.102, acc=1.000]
Epochs:  53%|█████▎    | 53/100 [00:06<00:04,  9.48it/s, t_loss=0.174, loss=0.102, acc=1.000]
Epochs:  53%|█████▎    | 53/100 [00:07<00:04,  9.48it/s, t_loss=0.181, loss=0.109, acc=1.000]
Epochs:  54%|█████▍    | 54/100 [00:07<00:04,  9.32it/s, t_loss=0.181, loss=0.109, acc=1.000]
Epochs:  54%|█████▍    | 54/100 [00:07<00:04,  9.32it/s, t_loss=0.090, loss=0.018, acc=1.000]
Epochs:  55%|█████▌    | 55/100 [00:07<00:04,  9.38it/s, t_loss=0.090, loss=0.018, acc=1.000]
Epochs:  55%|█████▌    | 55/100 [00:07<00:04,  9.38it/s, t_loss=0.095, loss=0.022, acc=1.000]
Epochs:  56%|█████▌    | 56/100 [00:07<00:04,  9.43it/s, t_loss=0.095, loss=0.022, acc=1.000]
Epochs:  56%|█████▌    | 56/100 [00:07<00:04,  9.43it/s, t_loss=0.099, loss=0.027, acc=1.000]
Epochs:  57%|█████▋    | 57/100 [00:07<00:04,  9.45it/s, t_loss=0.099, loss=0.027, acc=1.000]
Epochs:  57%|█████▋    | 57/100 [00:07<00:04,  9.45it/s, t_loss=0.176, loss=0.104, acc=1.000]
Epochs:  58%|█████▊    | 58/100 [00:07<00:04,  9.40it/s, t_loss=0.176, loss=0.104, acc=1.000]
Epochs:  58%|█████▊    | 58/100 [00:07<00:04,  9.40it/s, t_loss=0.100, loss=0.028, acc=1.000]
Epochs:  59%|█████▉    | 59/100 [00:07<00:04,  9.52it/s, t_loss=0.100, loss=0.028, acc=1.000]
Epochs:  59%|█████▉    | 59/100 [00:07<00:04,  9.52it/s, t_loss=0.113, loss=0.041, acc=1.000]
Epochs:  59%|█████▉    | 59/100 [00:07<00:04,  9.52it/s, t_loss=0.104, loss=0.031, acc=1.000]
Epochs:  61%|██████    | 61/100 [00:07<00:04,  9.69it/s, t_loss=0.104, loss=0.031, acc=1.000]
Epochs:  61%|██████    | 61/100 [00:07<00:04,  9.69it/s, t_loss=0.083, loss=0.011, acc=1.000]
Epochs:  61%|██████    | 61/100 [00:08<00:04,  9.69it/s, t_loss=0.092, loss=0.019, acc=1.000]
Epochs:  63%|██████▎   | 63/100 [00:08<00:03,  9.78it/s, t_loss=0.092, loss=0.019, acc=1.000]
Epochs:  63%|██████▎   | 63/100 [00:08<00:03,  9.78it/s, t_loss=0.088, loss=0.015, acc=1.000]
Epochs:  64%|██████▍   | 64/100 [00:08<00:03,  9.84it/s, t_loss=0.088, loss=0.015, acc=1.000]
Epochs:  64%|██████▍   | 64/100 [00:08<00:03,  9.84it/s, t_loss=0.127, loss=0.055, acc=1.000]
Epochs:  64%|██████▍   | 64/100 [00:08<00:03,  9.84it/s, t_loss=0.110, loss=0.038, acc=1.000]
Epochs:  66%|██████▌   | 66/100 [00:08<00:03,  9.80it/s, t_loss=0.110, loss=0.038, acc=1.000]
Epochs:  66%|██████▌   | 66/100 [00:08<00:03,  9.80it/s, t_loss=0.081, loss=0.009, acc=1.000]
Epochs:  66%|██████▌   | 66/100 [00:08<00:03,  9.80it/s, t_loss=0.082, loss=0.009, acc=1.000]
Epochs:  68%|██████▊   | 68/100 [00:08<00:03,  9.85it/s, t_loss=0.082, loss=0.009, acc=1.000]
Epochs:  68%|██████▊   | 68/100 [00:08<00:03,  9.85it/s, t_loss=0.083, loss=0.010, acc=1.000]
Epochs:  69%|██████▉   | 69/100 [00:08<00:03,  9.80it/s, t_loss=0.083, loss=0.010, acc=1.000]
Epochs:  69%|██████▉   | 69/100 [00:08<00:03,  9.80it/s, t_loss=0.078, loss=0.005, acc=1.000]
Epochs:  70%|███████   | 70/100 [00:08<00:03,  9.83it/s, t_loss=0.078, loss=0.005, acc=1.000]
Epochs:  70%|███████   | 70/100 [00:08<00:03,  9.83it/s, t_loss=0.092, loss=0.020, acc=1.000]
Epochs:  71%|███████   | 71/100 [00:08<00:02,  9.86it/s, t_loss=0.092, loss=0.020, acc=1.000]
Epochs:  71%|███████   | 71/100 [00:08<00:02,  9.86it/s, t_loss=0.095, loss=0.023, acc=1.000]
Epochs:  71%|███████   | 71/100 [00:09<00:02,  9.86it/s, t_loss=0.081, loss=0.009, acc=1.000]
Epochs:  73%|███████▎  | 73/100 [00:09<00:02,  9.92it/s, t_loss=0.081, loss=0.009, acc=1.000]
Epochs:  73%|███████▎  | 73/100 [00:09<00:02,  9.92it/s, t_loss=0.126, loss=0.054, acc=1.000]
Epochs:  74%|███████▍  | 74/100 [00:09<00:02,  9.91it/s, t_loss=0.126, loss=0.054, acc=1.000]
Epochs:  74%|███████▍  | 74/100 [00:09<00:02,  9.91it/s, t_loss=0.083, loss=0.010, acc=1.000]
Epochs:  74%|███████▍  | 74/100 [00:09<00:02,  9.91it/s, t_loss=0.105, loss=0.033, acc=1.000]
Epochs:  76%|███████▌  | 76/100 [00:09<00:02, 10.04it/s, t_loss=0.105, loss=0.033, acc=1.000]
Epochs:  76%|███████▌  | 76/100 [00:09<00:02, 10.04it/s, t_loss=0.075, loss=0.003, acc=1.000]
Epochs:  76%|███████▌  | 76/100 [00:09<00:02, 10.04it/s, t_loss=0.096, loss=0.024, acc=1.000]
Epochs:  78%|███████▊  | 78/100 [00:09<00:02, 10.03it/s, t_loss=0.096, loss=0.024, acc=1.000]
Epochs:  78%|███████▊  | 78/100 [00:09<00:02, 10.03it/s, t_loss=0.079, loss=0.007, acc=1.000]
Epochs:  78%|███████▊  | 78/100 [00:09<00:02, 10.03it/s, t_loss=0.145, loss=0.073, acc=1.000]
Epochs:  80%|████████  | 80/100 [00:09<00:01, 10.11it/s, t_loss=0.145, loss=0.073, acc=1.000]
Epochs:  80%|████████  | 80/100 [00:09<00:01, 10.11it/s, t_loss=0.081, loss=0.009, acc=1.000]
Epochs:  80%|████████  | 80/100 [00:09<00:01, 10.11it/s, t_loss=0.084, loss=0.012, acc=1.000]
Epochs:  82%|████████▏ | 82/100 [00:09<00:01, 10.20it/s, t_loss=0.084, loss=0.012, acc=1.000]
Epochs:  82%|████████▏ | 82/100 [00:09<00:01, 10.20it/s, t_loss=0.108, loss=0.036, acc=1.000]
Epochs:  82%|████████▏ | 82/100 [00:10<00:01, 10.20it/s, t_loss=0.090, loss=0.018, acc=1.000]
Epochs:  84%|████████▍ | 84/100 [00:10<00:01, 10.26it/s, t_loss=0.090, loss=0.018, acc=1.000]
Epochs:  84%|████████▍ | 84/100 [00:10<00:01, 10.26it/s, t_loss=0.082, loss=0.010, acc=1.000]
Epochs:  84%|████████▍ | 84/100 [00:10<00:01, 10.26it/s, t_loss=0.074, loss=0.002, acc=1.000]
Epochs:  86%|████████▌ | 86/100 [00:10<00:01, 10.39it/s, t_loss=0.074, loss=0.002, acc=1.000]
Epochs:  86%|████████▌ | 86/100 [00:10<00:01, 10.39it/s, t_loss=0.114, loss=0.042, acc=1.000]
Epochs:  86%|████████▌ | 86/100 [00:10<00:01, 10.39it/s, t_loss=0.087, loss=0.015, acc=1.000]
Epochs:  88%|████████▊ | 88/100 [00:10<00:01, 10.42it/s, t_loss=0.087, loss=0.015, acc=1.000]
Epochs:  88%|████████▊ | 88/100 [00:10<00:01, 10.42it/s, t_loss=0.084, loss=0.012, acc=1.000]
Epochs:  88%|████████▊ | 88/100 [00:10<00:01, 10.42it/s, t_loss=0.079, loss=0.007, acc=1.000]
Epochs:  90%|█████████ | 90/100 [00:10<00:00, 10.31it/s, t_loss=0.079, loss=0.007, acc=1.000]
Epochs:  90%|█████████ | 90/100 [00:10<00:00, 10.31it/s, t_loss=0.433, loss=0.361, acc=1.000]
Epochs:  90%|█████████ | 90/100 [00:10<00:00, 10.31it/s, t_loss=0.115, loss=0.043, acc=1.000]
Epochs:  92%|█████████▏| 92/100 [00:10<00:00, 10.43it/s, t_loss=0.115, loss=0.043, acc=1.000]
Epochs:  92%|█████████▏| 92/100 [00:10<00:00, 10.43it/s, t_loss=0.087, loss=0.015, acc=1.000]
Epochs:  92%|█████████▏| 92/100 [00:11<00:00, 10.43it/s, t_loss=0.079, loss=0.008, acc=1.000]
Epochs:  94%|█████████▍| 94/100 [00:11<00:00, 10.44it/s, t_loss=0.079, loss=0.008, acc=1.000]
Epochs:  94%|█████████▍| 94/100 [00:11<00:00, 10.44it/s, t_loss=0.108, loss=0.036, acc=1.000]
Epochs:  94%|█████████▍| 94/100 [00:11<00:00, 10.44it/s, t_loss=0.109, loss=0.038, acc=1.000]
Epochs:  96%|█████████▌| 96/100 [00:11<00:00, 10.47it/s, t_loss=0.109, loss=0.038, acc=1.000]
Epochs:  96%|█████████▌| 96/100 [00:11<00:00, 10.47it/s, t_loss=0.131, loss=0.059, acc=1.000]
Epochs:  96%|█████████▌| 96/100 [00:11<00:00, 10.47it/s, t_loss=0.141, loss=0.069, acc=1.000]
Epochs:  98%|█████████▊| 98/100 [00:11<00:00, 10.50it/s, t_loss=0.141, loss=0.069, acc=1.000]
Epochs:  98%|█████████▊| 98/100 [00:11<00:00, 10.50it/s, t_loss=0.085, loss=0.014, acc=1.000]
Epochs:  98%|█████████▊| 98/100 [00:11<00:00, 10.50it/s, t_loss=0.085, loss=0.013, acc=1.000]
Epochs: 100%|██████████| 100/100 [00:11<00:00, 10.59it/s, t_loss=0.085, loss=0.013, acc=1.000]
Epochs: 100%|██████████| 100/100 [00:11<00:00,  8.61it/s, t_loss=0.085, loss=0.013, acc=1.000]
2020-05-31 18:05:01 INFO     rasa.utils.tensorflow.models  - Finished training.
2020-05-31 18:05:01 INFO     rasa.core.agent  - Persisted model to '/tmp/tmpha6sd3hw/core'
2020-05-31 18:05:01 INFO     rasa.nlu.training_data.training_data  - Training data stats:
2020-05-31 18:05:01 INFO     rasa.nlu.training_data.training_data  - Number of intent examples: 43 (7 distinct intents)
2020-05-31 18:05:01 INFO     rasa.nlu.training_data.training_data  -   Found intents: 'affirm', 'bot_challenge', 'goodbye', 'mood_great', 'mood_unhappy', 'greet', 'deny'
2020-05-31 18:05:01 INFO     rasa.nlu.training_data.training_data  - Number of response examples: 0 (0 distinct responses)
2020-05-31 18:05:01 INFO     rasa.nlu.training_data.training_data  - Number of entity examples: 0 (0 distinct entities)
2020-05-31 18:05:01 INFO     rasa.nlu.model  - Starting to train component WhitespaceTokenizer
2020-05-31 18:05:01 INFO     rasa.nlu.model  - Finished training component.
2020-05-31 18:05:01 INFO     rasa.nlu.model  - Starting to train component RegexFeaturizer
2020-05-31 18:05:01 INFO     rasa.nlu.model  - Finished training component.
2020-05-31 18:05:01 INFO     rasa.nlu.model  - Starting to train component LexicalSyntacticFeaturizer
2020-05-31 18:05:01 INFO     rasa.nlu.model  - Finished training component.
2020-05-31 18:05:01 INFO     rasa.nlu.model  - Starting to train component CountVectorsFeaturizer
2020-05-31 18:05:01 INFO     rasa.nlu.model  - Finished training component.
2020-05-31 18:05:01 INFO     rasa.nlu.model  - Starting to train component CountVectorsFeaturizer
2020-05-31 18:05:01 INFO     rasa.nlu.model  - Finished training component.
2020-05-31 18:05:01 INFO     rasa.nlu.model  - Starting to train component DIETClassifier
/opt/venv/lib/python3.7/site-packages/rasa/utils/common.py:364: UserWarning: You specified 'DIET' to train entities, but no entities are present in the training data. Skip training of entities.

Epochs:   0%|          | 0/100 [00:00<?, ?it/s]
Epochs:   0%|          | 0/100 [00:00<?, ?it/s, t_loss=12.399, i_loss=11.040, i_acc=0.140]
Epochs:   1%|          | 1/100 [00:00<00:17,  5.77it/s, t_loss=12.399, i_loss=11.040, i_acc=0.140]
Epochs:   1%|          | 1/100 [00:00<00:17,  5.77it/s, t_loss=7.754, i_loss=6.394, i_acc=0.186]  
Epochs:   2%|▏         | 2/100 [00:00<00:16,  5.81it/s, t_loss=7.754, i_loss=6.394, i_acc=0.186]
Epochs:   2%|▏         | 2/100 [00:00<00:16,  5.81it/s, t_loss=7.160, i_loss=5.801, i_acc=0.233]
Epochs:   3%|▎         | 3/100 [00:00<00:17,  5.67it/s, t_loss=7.160, i_loss=5.801, i_acc=0.233]
Epochs:   3%|▎         | 3/100 [00:00<00:17,  5.67it/s, t_loss=8.201, i_loss=6.841, i_acc=0.209]
Epochs:   4%|▍         | 4/100 [00:00<00:16,  5.79it/s, t_loss=8.201, i_loss=6.841, i_acc=0.209]
Epochs:   4%|▍         | 4/100 [00:00<00:16,  5.79it/s, t_loss=7.860, i_loss=6.500, i_acc=0.186]
Epochs:   5%|▌         | 5/100 [00:00<00:16,  5.80it/s, t_loss=7.860, i_loss=6.500, i_acc=0.186]
Epochs:   5%|▌         | 5/100 [00:01<00:16,  5.80it/s, t_loss=6.972, i_loss=5.611, i_acc=0.302]
Epochs:   6%|▌         | 6/100 [00:01<00:15,  5.88it/s, t_loss=6.972, i_loss=5.611, i_acc=0.302]
Epochs:   6%|▌         | 6/100 [00:01<00:15,  5.88it/s, t_loss=6.288, i_loss=4.926, i_acc=0.302]
Epochs:   7%|▋         | 7/100 [00:01<00:15,  5.92it/s, t_loss=6.288, i_loss=4.926, i_acc=0.302]
Epochs:   7%|▋         | 7/100 [00:01<00:15,  5.92it/s, t_loss=6.591, i_loss=5.228, i_acc=0.419]
Epochs:   8%|▊         | 8/100 [00:01<00:15,  5.91it/s, t_loss=6.591, i_loss=5.228, i_acc=0.419]
Epochs:   8%|▊         | 8/100 [00:01<00:15,  5.91it/s, t_loss=5.677, i_loss=4.314, i_acc=0.488]
Epochs:   9%|▉         | 9/100 [00:01<00:15,  5.96it/s, t_loss=5.677, i_loss=4.314, i_acc=0.488]
Epochs:   9%|▉         | 9/100 [00:01<00:15,  5.96it/s, t_loss=5.627, i_loss=4.263, i_acc=0.488]
Epochs:  10%|█         | 10/100 [00:01<00:15,  5.99it/s, t_loss=5.627, i_loss=4.263, i_acc=0.488]
Epochs:  10%|█         | 10/100 [00:01<00:15,  5.99it/s, t_loss=5.754, i_loss=4.389, i_acc=0.488]
Epochs:  11%|█         | 11/100 [00:01<00:14,  5.99it/s, t_loss=5.754, i_loss=4.389, i_acc=0.488]
Epochs:  11%|█         | 11/100 [00:02<00:14,  5.99it/s, t_loss=5.484, i_loss=4.118, i_acc=0.535]
Epochs:  12%|█▏        | 12/100 [00:02<00:14,  6.02it/s, t_loss=5.484, i_loss=4.118, i_acc=0.535]
Epochs:  12%|█▏        | 12/100 [00:02<00:14,  6.02it/s, t_loss=5.437, i_loss=4.071, i_acc=0.581]
Epochs:  13%|█▎        | 13/100 [00:02<00:14,  6.06it/s, t_loss=5.437, i_loss=4.071, i_acc=0.581]
Epochs:  13%|█▎        | 13/100 [00:02<00:14,  6.06it/s, t_loss=5.587, i_loss=4.220, i_acc=0.767]
Epochs:  14%|█▍        | 14/100 [00:02<00:14,  6.09it/s, t_loss=5.587, i_loss=4.220, i_acc=0.767]
Epochs:  14%|█▍        | 14/100 [00:02<00:14,  6.09it/s, t_loss=5.009, i_loss=3.642, i_acc=0.698]
Epochs:  15%|█▌        | 15/100 [00:02<00:13,  6.10it/s, t_loss=5.009, i_loss=3.642, i_acc=0.698]
Epochs:  15%|█▌        | 15/100 [00:02<00:13,  6.10it/s, t_loss=4.644, i_loss=3.276, i_acc=0.767]
Epochs:  16%|█▌        | 16/100 [00:02<00:13,  6.10it/s, t_loss=4.644, i_loss=3.276, i_acc=0.767]
Epochs:  16%|█▌        | 16/100 [00:02<00:13,  6.10it/s, t_loss=4.802, i_loss=3.433, i_acc=0.698]
Epochs:  17%|█▋        | 17/100 [00:02<00:13,  5.99it/s, t_loss=4.802, i_loss=3.433, i_acc=0.698]
Epochs:  17%|█▋        | 17/100 [00:03<00:13,  5.99it/s, t_loss=4.709, i_loss=3.340, i_acc=0.791]
Epochs:  18%|█▊        | 18/100 [00:03<00:13,  6.00it/s, t_loss=4.709, i_loss=3.340, i_acc=0.791]
Epochs:  18%|█▊        | 18/100 [00:03<00:13,  6.00it/s, t_loss=4.424, i_loss=3.054, i_acc=0.744]
Epochs:  19%|█▉        | 19/100 [00:03<00:13,  6.02it/s, t_loss=4.424, i_loss=3.054, i_acc=0.744]
Epochs:  19%|█▉        | 19/100 [00:03<00:13,  6.02it/s, t_loss=4.520, i_loss=3.150, i_acc=0.767]
Epochs:  20%|██        | 20/100 [00:03<00:13,  6.01it/s, t_loss=4.520, i_loss=3.150, i_acc=0.767]
Epochs:  20%|██        | 20/100 [00:03<00:13,  6.01it/s, t_loss=4.241, i_loss=2.870, i_acc=0.884]
Epochs:  21%|██        | 21/100 [00:03<00:13,  6.02it/s, t_loss=4.241, i_loss=2.870, i_acc=0.884]
Epochs:  21%|██        | 21/100 [00:03<00:13,  6.02it/s, t_loss=4.239, i_loss=2.868, i_acc=0.791]
Epochs:  22%|██▏       | 22/100 [00:03<00:12,  6.05it/s, t_loss=4.239, i_loss=2.868, i_acc=0.791]
Epochs:  22%|██▏       | 22/100 [00:03<00:12,  6.05it/s, t_loss=4.080, i_loss=2.709, i_acc=0.884]
Epochs:  23%|██▎       | 23/100 [00:03<00:12,  6.03it/s, t_loss=4.080, i_loss=2.709, i_acc=0.884]
Epochs:  23%|██▎       | 23/100 [00:04<00:12,  6.03it/s, t_loss=4.151, i_loss=2.779, i_acc=0.837]
Epochs:  24%|██▍       | 24/100 [00:04<00:12,  6.05it/s, t_loss=4.151, i_loss=2.779, i_acc=0.837]
Epochs:  24%|██▍       | 24/100 [00:04<00:12,  6.05it/s, t_loss=4.154, i_loss=2.782, i_acc=0.930]
Epochs:  25%|██▌       | 25/100 [00:04<00:12,  6.02it/s, t_loss=4.154, i_loss=2.782, i_acc=0.930]
Epochs:  25%|██▌       | 25/100 [00:04<00:12,  6.02it/s, t_loss=3.917, i_loss=2.544, i_acc=0.837]
Epochs:  26%|██▌       | 26/100 [00:04<00:12,  6.05it/s, t_loss=3.917, i_loss=2.544, i_acc=0.837]
Epochs:  26%|██▌       | 26/100 [00:04<00:12,  6.05it/s, t_loss=3.865, i_loss=2.492, i_acc=0.860]
Epochs:  27%|██▋       | 27/100 [00:04<00:12,  5.86it/s, t_loss=3.865, i_loss=2.492, i_acc=0.860]
Epochs:  27%|██▋       | 27/100 [00:04<00:12,  5.86it/s, t_loss=3.592, i_loss=2.218, i_acc=0.837]
Epochs:  28%|██▊       | 28/100 [00:04<00:12,  5.83it/s, t_loss=3.592, i_loss=2.218, i_acc=0.837]
Epochs:  28%|██▊       | 28/100 [00:04<00:12,  5.83it/s, t_loss=3.685, i_loss=2.310, i_acc=0.884]
Epochs:  29%|██▉       | 29/100 [00:04<00:11,  5.94it/s, t_loss=3.685, i_loss=2.310, i_acc=0.884]
Epochs:  29%|██▉       | 29/100 [00:05<00:11,  5.94it/s, t_loss=3.642, i_loss=2.267, i_acc=0.977]
Epochs:  30%|███       | 30/100 [00:05<00:11,  5.96it/s, t_loss=3.642, i_loss=2.267, i_acc=0.977]
Epochs:  30%|███       | 30/100 [00:05<00:11,  5.96it/s, t_loss=3.485, i_loss=2.110, i_acc=0.930]
Epochs:  31%|███       | 31/100 [00:05<00:11,  5.94it/s, t_loss=3.485, i_loss=2.110, i_acc=0.930]
Epochs:  31%|███       | 31/100 [00:05<00:11,  5.94it/s, t_loss=3.445, i_loss=2.070, i_acc=0.953]
Epochs:  32%|███▏      | 32/100 [00:05<00:11,  5.95it/s, t_loss=3.445, i_loss=2.070, i_acc=0.953]
Epochs:  32%|███▏      | 32/100 [00:05<00:11,  5.95it/s, t_loss=3.239, i_loss=1.862, i_acc=0.930]
Epochs:  33%|███▎      | 33/100 [00:05<00:11,  5.99it/s, t_loss=3.239, i_loss=1.862, i_acc=0.930]
Epochs:  33%|███▎      | 33/100 [00:05<00:11,  5.99it/s, t_loss=3.322, i_loss=1.945, i_acc=0.930]
Epochs:  34%|███▍      | 34/100 [00:05<00:10,  6.01it/s, t_loss=3.322, i_loss=1.945, i_acc=0.930]
Epochs:  34%|███▍      | 34/100 [00:05<00:10,  6.01it/s, t_loss=3.328, i_loss=1.951, i_acc=0.907]
Epochs:  35%|███▌      | 35/100 [00:05<00:10,  6.02it/s, t_loss=3.328, i_loss=1.951, i_acc=0.907]
Epochs:  35%|███▌      | 35/100 [00:06<00:10,  6.02it/s, t_loss=2.989, i_loss=1.611, i_acc=0.907]
Epochs:  36%|███▌      | 36/100 [00:06<00:10,  6.08it/s, t_loss=2.989, i_loss=1.611, i_acc=0.907]
Epochs:  36%|███▌      | 36/100 [00:06<00:10,  6.08it/s, t_loss=3.135, i_loss=1.757, i_acc=0.953]
Epochs:  37%|███▋      | 37/100 [00:06<00:10,  6.09it/s, t_loss=3.135, i_loss=1.757, i_acc=0.953]
Epochs:  37%|███▋      | 37/100 [00:06<00:10,  6.09it/s, t_loss=3.121, i_loss=1.742, i_acc=0.930]
Epochs:  38%|███▊      | 38/100 [00:06<00:10,  6.12it/s, t_loss=3.121, i_loss=1.742, i_acc=0.930]
Epochs:  38%|███▊      | 38/100 [00:06<00:10,  6.12it/s, t_loss=2.805, i_loss=1.427, i_acc=0.977]
Epochs:  39%|███▉      | 39/100 [00:06<00:09,  6.15it/s, t_loss=2.805, i_loss=1.427, i_acc=0.977]
Epochs:  39%|███▉      | 39/100 [00:06<00:09,  6.15it/s, t_loss=2.853, i_loss=1.474, i_acc=0.977]
Epochs:  40%|████      | 40/100 [00:06<00:09,  6.09it/s, t_loss=2.853, i_loss=1.474, i_acc=0.977]
Epochs:  40%|████      | 40/100 [00:06<00:09,  6.09it/s, t_loss=2.744, i_loss=1.365, i_acc=0.977]
Epochs:  41%|████      | 41/100 [00:06<00:09,  6.13it/s, t_loss=2.744, i_loss=1.365, i_acc=0.977]
Epochs:  41%|████      | 41/100 [00:06<00:09,  6.13it/s, t_loss=2.661, i_loss=1.282, i_acc=0.953]
Epochs:  42%|████▏     | 42/100 [00:06<00:09,  6.13it/s, t_loss=2.661, i_loss=1.282, i_acc=0.953]
Epochs:  42%|████▏     | 42/100 [00:07<00:09,  6.13it/s, t_loss=2.809, i_loss=1.429, i_acc=0.977]
Epochs:  43%|████▎     | 43/100 [00:07<00:09,  6.13it/s, t_loss=2.809, i_loss=1.429, i_acc=0.977]
Epochs:  43%|████▎     | 43/100 [00:07<00:09,  6.13it/s, t_loss=2.717, i_loss=1.337, i_acc=0.930]
Epochs:  44%|████▍     | 44/100 [00:07<00:09,  6.10it/s, t_loss=2.717, i_loss=1.337, i_acc=0.930]
Epochs:  44%|████▍     | 44/100 [00:07<00:09,  6.10it/s, t_loss=2.717, i_loss=1.337, i_acc=0.977]
Epochs:  45%|████▌     | 45/100 [00:07<00:09,  6.08it/s, t_loss=2.717, i_loss=1.337, i_acc=0.977]
Epochs:  45%|████▌     | 45/100 [00:07<00:09,  6.08it/s, t_loss=2.572, i_loss=1.192, i_acc=0.977]
Epochs:  46%|████▌     | 46/100 [00:07<00:08,  6.07it/s, t_loss=2.572, i_loss=1.192, i_acc=0.977]
Epochs:  46%|████▌     | 46/100 [00:07<00:08,  6.07it/s, t_loss=2.530, i_loss=1.150, i_acc=0.953]
Epochs:  47%|████▋     | 47/100 [00:07<00:08,  6.07it/s, t_loss=2.530, i_loss=1.150, i_acc=0.953]
Epochs:  47%|████▋     | 47/100 [00:07<00:08,  6.07it/s, t_loss=2.434, i_loss=1.053, i_acc=0.953]
Epochs:  48%|████▊     | 48/100 [00:07<00:08,  6.07it/s, t_loss=2.434, i_loss=1.053, i_acc=0.953]
Epochs:  48%|████▊     | 48/100 [00:08<00:08,  6.07it/s, t_loss=2.556, i_loss=1.175, i_acc=0.977]
Epochs:  49%|████▉     | 49/100 [00:08<00:08,  6.09it/s, t_loss=2.556, i_loss=1.175, i_acc=0.977]
Epochs:  49%|████▉     | 49/100 [00:08<00:08,  6.09it/s, t_loss=2.647, i_loss=1.266, i_acc=0.977]
Epochs:  50%|█████     | 50/100 [00:08<00:08,  6.09it/s, t_loss=2.647, i_loss=1.266, i_acc=0.977]
Epochs:  50%|█████     | 50/100 [00:08<00:08,  6.09it/s, t_loss=2.480, i_loss=1.098, i_acc=0.953]
Epochs:  51%|█████     | 51/100 [00:08<00:08,  5.96it/s, t_loss=2.480, i_loss=1.098, i_acc=0.953]
Epochs:  51%|█████     | 51/100 [00:08<00:08,  5.96it/s, t_loss=2.377, i_loss=0.995, i_acc=1.000]
Epochs:  52%|█████▏    | 52/100 [00:08<00:08,  5.97it/s, t_loss=2.377, i_loss=0.995, i_acc=1.000]
Epochs:  52%|█████▏    | 52/100 [00:08<00:08,  5.97it/s, t_loss=2.446, i_loss=1.064, i_acc=1.000]
Epochs:  53%|█████▎    | 53/100 [00:08<00:07,  5.98it/s, t_loss=2.446, i_loss=1.064, i_acc=1.000]
Epochs:  53%|█████▎    | 53/100 [00:08<00:07,  5.98it/s, t_loss=2.416, i_loss=1.033, i_acc=1.000]
Epochs:  54%|█████▍    | 54/100 [00:08<00:07,  6.01it/s, t_loss=2.416, i_loss=1.033, i_acc=1.000]
Epochs:  54%|█████▍    | 54/100 [00:09<00:07,  6.01it/s, t_loss=2.271, i_loss=0.889, i_acc=1.000]
Epochs:  55%|█████▌    | 55/100 [00:09<00:07,  6.00it/s, t_loss=2.271, i_loss=0.889, i_acc=1.000]
Epochs:  55%|█████▌    | 55/100 [00:09<00:07,  6.00it/s, t_loss=2.394, i_loss=1.012, i_acc=1.000]
Epochs:  56%|█████▌    | 56/100 [00:09<00:07,  5.98it/s, t_loss=2.394, i_loss=1.012, i_acc=1.000]
Epochs:  56%|█████▌    | 56/100 [00:09<00:07,  5.98it/s, t_loss=2.262, i_loss=0.879, i_acc=1.000]
Epochs:  57%|█████▋    | 57/100 [00:09<00:07,  6.01it/s, t_loss=2.262, i_loss=0.879, i_acc=1.000]
Epochs:  57%|█████▋    | 57/100 [00:09<00:07,  6.01it/s, t_loss=2.129, i_loss=0.746, i_acc=1.000]
Epochs:  58%|█████▊    | 58/100 [00:09<00:06,  6.04it/s, t_loss=2.129, i_loss=0.746, i_acc=1.000]
Epochs:  58%|█████▊    | 58/100 [00:09<00:06,  6.04it/s, t_loss=2.179, i_loss=0.795, i_acc=0.977]
Epochs:  59%|█████▉    | 59/100 [00:09<00:06,  6.07it/s, t_loss=2.179, i_loss=0.795, i_acc=0.977]
Epochs:  59%|█████▉    | 59/100 [00:09<00:06,  6.07it/s, t_loss=2.149, i_loss=0.766, i_acc=0.977]
Epochs:  60%|██████    | 60/100 [00:09<00:06,  6.07it/s, t_loss=2.149, i_loss=0.766, i_acc=0.977]
Epochs:  60%|██████    | 60/100 [00:10<00:06,  6.07it/s, t_loss=1.937, i_loss=0.554, i_acc=0.977]
Epochs:  61%|██████    | 61/100 [00:10<00:06,  6.07it/s, t_loss=1.937, i_loss=0.554, i_acc=0.977]
Epochs:  61%|██████    | 61/100 [00:10<00:06,  6.07it/s, t_loss=1.958, i_loss=0.575, i_acc=1.000]
Epochs:  62%|██████▏   | 62/100 [00:10<00:06,  6.01it/s, t_loss=1.958, i_loss=0.575, i_acc=1.000]
Epochs:  62%|██████▏   | 62/100 [00:10<00:06,  6.01it/s, t_loss=2.008, i_loss=0.624, i_acc=1.000]
Epochs:  63%|██████▎   | 63/100 [00:10<00:06,  5.94it/s, t_loss=2.008, i_loss=0.624, i_acc=1.000]
Epochs:  63%|██████▎   | 63/100 [00:10<00:06,  5.94it/s, t_loss=1.971, i_loss=0.587, i_acc=1.000]
Epochs:  64%|██████▍   | 64/100 [00:10<00:05,  6.03it/s, t_loss=1.971, i_loss=0.587, i_acc=1.000]
Epochs:  64%|██████▍   | 64/100 [00:10<00:05,  6.03it/s, t_loss=2.141, i_loss=0.757, i_acc=0.977]
Epochs:  65%|██████▌   | 65/100 [00:10<00:05,  6.09it/s, t_loss=2.141, i_loss=0.757, i_acc=0.977]
Epochs:  65%|██████▌   | 65/100 [00:10<00:05,  6.09it/s, t_loss=2.032, i_loss=0.648, i_acc=1.000]
Epochs:  66%|██████▌   | 66/100 [00:10<00:05,  6.11it/s, t_loss=2.032, i_loss=0.648, i_acc=1.000]
Epochs:  66%|██████▌   | 66/100 [00:11<00:05,  6.11it/s, t_loss=1.893, i_loss=0.508, i_acc=0.977]
Epochs:  67%|██████▋   | 67/100 [00:11<00:05,  6.11it/s, t_loss=1.893, i_loss=0.508, i_acc=0.977]
Epochs:  67%|██████▋   | 67/100 [00:11<00:05,  6.11it/s, t_loss=2.067, i_loss=0.683, i_acc=1.000]
Epochs:  68%|██████▊   | 68/100 [00:11<00:05,  6.06it/s, t_loss=2.067, i_loss=0.683, i_acc=1.000]
Epochs:  68%|██████▊   | 68/100 [00:11<00:05,  6.06it/s, t_loss=2.047, i_loss=0.662, i_acc=0.977]
Epochs:  69%|██████▉   | 69/100 [00:11<00:05,  6.06it/s, t_loss=2.047, i_loss=0.662, i_acc=0.977]
Epochs:  69%|██████▉   | 69/100 [00:11<00:05,  6.06it/s, t_loss=1.788, i_loss=0.404, i_acc=1.000]
Epochs:  70%|███████   | 70/100 [00:11<00:04,  6.08it/s, t_loss=1.788, i_loss=0.404, i_acc=1.000]
Epochs:  70%|███████   | 70/100 [00:11<00:04,  6.08it/s, t_loss=1.950, i_loss=0.565, i_acc=1.000]
Epochs:  71%|███████   | 71/100 [00:11<00:04,  6.13it/s, t_loss=1.950, i_loss=0.565, i_acc=1.000]
Epochs:  71%|███████   | 71/100 [00:11<00:04,  6.13it/s, t_loss=1.896, i_loss=0.511, i_acc=1.000]
Epochs:  72%|███████▏  | 72/100 [00:11<00:04,  6.15it/s, t_loss=1.896, i_loss=0.511, i_acc=1.000]
Epochs:  72%|███████▏  | 72/100 [00:12<00:04,  6.15it/s, t_loss=1.718, i_loss=0.333, i_acc=0.977]
Epochs:  73%|███████▎  | 73/100 [00:12<00:04,  6.16it/s, t_loss=1.718, i_loss=0.333, i_acc=0.977]
Epochs:  73%|███████▎  | 73/100 [00:12<00:04,  6.16it/s, t_loss=1.920, i_loss=0.535, i_acc=1.000]
Epochs:  74%|███████▍  | 74/100 [00:12<00:04,  5.98it/s, t_loss=1.920, i_loss=0.535, i_acc=1.000]
Epochs:  74%|███████▍  | 74/100 [00:12<00:04,  5.98it/s, t_loss=1.828, i_loss=0.444, i_acc=1.000]
Epochs:  75%|███████▌  | 75/100 [00:12<00:04,  6.00it/s, t_loss=1.828, i_loss=0.444, i_acc=1.000]
Epochs:  75%|███████▌  | 75/100 [00:12<00:04,  6.00it/s, t_loss=1.828, i_loss=0.444, i_acc=1.000]
Epochs:  76%|███████▌  | 76/100 [00:12<00:03,  6.02it/s, t_loss=1.828, i_loss=0.444, i_acc=1.000]
Epochs:  76%|███████▌  | 76/100 [00:12<00:03,  6.02it/s, t_loss=1.825, i_loss=0.440, i_acc=1.000]
Epochs:  77%|███████▋  | 77/100 [00:12<00:03,  6.05it/s, t_loss=1.825, i_loss=0.440, i_acc=1.000]
Epochs:  77%|███████▋  | 77/100 [00:12<00:03,  6.05it/s, t_loss=1.914, i_loss=0.529, i_acc=1.000]
Epochs:  78%|███████▊  | 78/100 [00:12<00:03,  6.09it/s, t_loss=1.914, i_loss=0.529, i_acc=1.000]
Epochs:  78%|███████▊  | 78/100 [00:13<00:03,  6.09it/s, t_loss=1.610, i_loss=0.226, i_acc=1.000]
Epochs:  79%|███████▉  | 79/100 [00:13<00:03,  6.11it/s, t_loss=1.610, i_loss=0.226, i_acc=1.000]
Epochs:  79%|███████▉  | 79/100 [00:13<00:03,  6.11it/s, t_loss=1.645, i_loss=0.260, i_acc=1.000]
Epochs:  80%|████████  | 80/100 [00:13<00:03,  6.14it/s, t_loss=1.645, i_loss=0.260, i_acc=1.000]
Epochs:  80%|████████  | 80/100 [00:13<00:03,  6.14it/s, t_loss=1.689, i_loss=0.305, i_acc=0.977]
Epochs:  81%|████████  | 81/100 [00:13<00:03,  6.16it/s, t_loss=1.689, i_loss=0.305, i_acc=0.977]
Epochs:  81%|████████  | 81/100 [00:13<00:03,  6.16it/s, t_loss=1.636, i_loss=0.251, i_acc=1.000]
Epochs:  82%|████████▏ | 82/100 [00:13<00:02,  6.17it/s, t_loss=1.636, i_loss=0.251, i_acc=1.000]
Epochs:  82%|████████▏ | 82/100 [00:13<00:02,  6.17it/s, t_loss=1.746, i_loss=0.361, i_acc=1.000]
Epochs:  83%|████████▎ | 83/100 [00:13<00:02,  6.20it/s, t_loss=1.746, i_loss=0.361, i_acc=1.000]
Epochs:  83%|████████▎ | 83/100 [00:13<00:02,  6.20it/s, t_loss=1.675, i_loss=0.290, i_acc=1.000]
Epochs:  84%|████████▍ | 84/100 [00:13<00:02,  6.20it/s, t_loss=1.675, i_loss=0.290, i_acc=1.000]
Epochs:  84%|████████▍ | 84/100 [00:14<00:02,  6.20it/s, t_loss=1.572, i_loss=0.188, i_acc=1.000]
Epochs:  85%|████████▌ | 85/100 [00:14<00:02,  6.18it/s, t_loss=1.572, i_loss=0.188, i_acc=1.000]
Epochs:  85%|████████▌ | 85/100 [00:14<00:02,  6.18it/s, t_loss=1.619, i_loss=0.235, i_acc=1.000]
Epochs:  86%|████████▌ | 86/100 [00:14<00:02,  6.04it/s, t_loss=1.619, i_loss=0.235, i_acc=1.000]
Epochs:  86%|████████▌ | 86/100 [00:14<00:02,  6.04it/s, t_loss=1.648, i_loss=0.264, i_acc=1.000]
Epochs:  87%|████████▋ | 87/100 [00:14<00:02,  6.00it/s, t_loss=1.648, i_loss=0.264, i_acc=1.000]
Epochs:  87%|████████▋ | 87/100 [00:14<00:02,  6.00it/s, t_loss=1.528, i_loss=0.144, i_acc=1.000]
Epochs:  88%|████████▊ | 88/100 [00:14<00:01,  6.02it/s, t_loss=1.528, i_loss=0.144, i_acc=1.000]
Epochs:  88%|████████▊ | 88/100 [00:14<00:01,  6.02it/s, t_loss=1.819, i_loss=0.435, i_acc=1.000]
Epochs:  89%|████████▉ | 89/100 [00:14<00:01,  6.06it/s, t_loss=1.819, i_loss=0.435, i_acc=1.000]
Epochs:  89%|████████▉ | 89/100 [00:14<00:01,  6.06it/s, t_loss=1.550, i_loss=0.167, i_acc=1.000]
Epochs:  90%|█████████ | 90/100 [00:14<00:01,  6.08it/s, t_loss=1.550, i_loss=0.167, i_acc=1.000]
Epochs:  90%|█████████ | 90/100 [00:15<00:01,  6.08it/s, t_loss=1.553, i_loss=0.169, i_acc=1.000]
Epochs:  91%|█████████ | 91/100 [00:15<00:01,  6.09it/s, t_loss=1.553, i_loss=0.169, i_acc=1.000]
Epochs:  91%|█████████ | 91/100 [00:15<00:01,  6.09it/s, t_loss=1.573, i_loss=0.190, i_acc=1.000]
Epochs:  92%|█████████▏| 92/100 [00:15<00:01,  6.10it/s, t_loss=1.573, i_loss=0.190, i_acc=1.000]
Epochs:  92%|█████████▏| 92/100 [00:15<00:01,  6.10it/s, t_loss=1.512, i_loss=0.129, i_acc=1.000]
Epochs:  93%|█████████▎| 93/100 [00:15<00:01,  6.08it/s, t_loss=1.512, i_loss=0.129, i_acc=1.000]
Epochs:  93%|█████████▎| 93/100 [00:15<00:01,  6.08it/s, t_loss=1.577, i_loss=0.194, i_acc=1.000]
Epochs:  94%|█████████▍| 94/100 [00:15<00:00,  6.08it/s, t_loss=1.577, i_loss=0.194, i_acc=1.000]
Epochs:  94%|█████████▍| 94/100 [00:15<00:00,  6.08it/s, t_loss=1.583, i_loss=0.200, i_acc=1.000]
Epochs:  95%|█████████▌| 95/100 [00:15<00:00,  6.08it/s, t_loss=1.583, i_loss=0.200, i_acc=1.000]
Epochs:  95%|█████████▌| 95/100 [00:15<00:00,  6.08it/s, t_loss=1.696, i_loss=0.314, i_acc=1.000]
Epochs:  96%|█████████▌| 96/100 [00:15<00:00,  6.09it/s, t_loss=1.696, i_loss=0.314, i_acc=1.000]
Epochs:  96%|█████████▌| 96/100 [00:16<00:00,  6.09it/s, t_loss=1.595, i_loss=0.213, i_acc=1.000]
Epochs:  97%|█████████▋| 97/100 [00:16<00:00,  6.00it/s, t_loss=1.595, i_loss=0.213, i_acc=1.000]
Epochs:  97%|█████████▋| 97/100 [00:16<00:00,  6.00it/s, t_loss=1.531, i_loss=0.149, i_acc=1.000]
Epochs:  98%|█████████▊| 98/100 [00:16<00:00,  6.03it/s, t_loss=1.531, i_loss=0.149, i_acc=1.000]
Epochs:  98%|█████████▊| 98/100 [00:16<00:00,  6.03it/s, t_loss=1.479, i_loss=0.097, i_acc=1.000]
Epochs:  99%|█████████▉| 99/100 [00:16<00:00,  6.03it/s, t_loss=1.479, i_loss=0.097, i_acc=1.000]
Epochs:  99%|█████████▉| 99/100 [00:16<00:00,  6.03it/s, t_loss=1.485, i_loss=0.104, i_acc=1.000]
Epochs: 100%|██████████| 100/100 [00:16<00:00,  6.06it/s, t_loss=1.485, i_loss=0.104, i_acc=1.000]
Epochs: 100%|██████████| 100/100 [00:16<00:00,  6.04it/s, t_loss=1.485, i_loss=0.104, i_acc=1.000]
2020-05-31 18:05:25 INFO     rasa.utils.tensorflow.models  - Finished training.
2020-05-31 18:05:25 INFO     rasa.nlu.model  - Finished training component.
2020-05-31 18:05:25 INFO     rasa.nlu.model  - Starting to train component EntitySynonymMapper
2020-05-31 18:05:25 INFO     rasa.nlu.model  - Finished training component.
2020-05-31 18:05:25 INFO     rasa.nlu.model  - Starting to train component ResponseSelector
2020-05-31 18:05:25 INFO     rasa.nlu.selectors.response_selector  - Retrieval intent parameter was left to its default value. This response selector will be trained on training examples combining all retrieval intents.
2020-05-31 18:05:25 INFO     rasa.nlu.model  - Finished training component.
2020-05-31 18:05:25 INFO     rasa.nlu.model  - Successfully saved model into '/tmp/tmpha6sd3hw/nlu'
Training Core model...
Core model training completed.
Training NLU model...
NLU model training completed.
Traceback (most recent call last):
  File "/opt/venv/bin/rasa", line 8, in <module>
    sys.exit(main())
  File "/opt/venv/lib/python3.7/site-packages/rasa/__main__.py", line 108, in main
    cmdline_arguments.func(cmdline_arguments)
  File "/opt/venv/lib/python3.7/site-packages/rasa/cli/train.py", line 77, in train
    nlu_additional_arguments=extract_nlu_additional_arguments(args),
  File "/opt/venv/lib/python3.7/site-packages/rasa/train.py", line 52, in train
    nlu_additional_arguments=nlu_additional_arguments,
  File "uvloop/loop.pyx", line 1456, in uvloop.loop.Loop.run_until_complete
  File "/opt/venv/lib/python3.7/site-packages/rasa/train.py", line 107, in train_async
    nlu_additional_arguments=nlu_additional_arguments,
  File "/opt/venv/lib/python3.7/site-packages/rasa/train.py", line 206, in _train_async_internal
    fixed_model_name=fixed_model_name,
  File "/opt/venv/lib/python3.7/site-packages/rasa/model.py", line 464, in package_model
    create_package_rasa(train_path, output_directory, fingerprint)
  File "/opt/venv/lib/python3.7/site-packages/rasa/model.py", line 258, in create_package_rasa
    os.makedirs(output_directory)
  File "/usr/local/lib/python3.7/os.py", line 223, in makedirs
    mkdir(name, mode)
PermissionError: [Errno 13] Permission denied: 'models'
The command '/bin/bash -o pipefail -c rasa train' returned a non-zero code: 1
ERROR
ERROR: build step 0 "gcr.io/cloud-builders/docker" failed: step exited with non-zero status: 1