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distilbert_finetune_own_data_model

Token Classification
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distilbert
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End of training

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  1. README.md +66 -66
  2. model.safetensors +1 -1
  3. runs/Mar04_09-17-06_561d3d140928/events.out.tfevents.1709543848.561d3d140928.219.4 +3 -0
  4. runs/Mar04_09-17-06_561d3d140928/events.out.tfevents.1709543872.561d3d140928.219.5 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6021
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- - Precision: 0.6429
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- - Recall: 0.75
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- - F1: 0.6923
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- - Accuracy: 0.9310
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  ## Model description
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@@ -43,7 +43,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -55,66 +55,66 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 7 | 0.4718 | 0.7692 | 0.8333 | 0.8 | 0.9483 |
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- | No log | 2.0 | 14 | 0.6303 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 3.0 | 21 | 0.6305 | 0.7692 | 0.8333 | 0.8 | 0.9310 |
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- | No log | 4.0 | 28 | 0.6725 | 0.7692 | 0.8333 | 0.8 | 0.9310 |
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- | No log | 5.0 | 35 | 0.7307 | 0.7692 | 0.8333 | 0.8 | 0.9310 |
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- | No log | 6.0 | 42 | 0.6282 | 0.7692 | 0.8333 | 0.8 | 0.9483 |
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- | No log | 7.0 | 49 | 0.9412 | 0.75 | 0.75 | 0.75 | 0.8793 |
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- | No log | 8.0 | 56 | 0.9923 | 0.8 | 0.6667 | 0.7273 | 0.8966 |
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- | No log | 9.0 | 63 | 1.0986 | 0.75 | 0.5 | 0.6 | 0.8966 |
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- | No log | 10.0 | 70 | 0.7721 | 0.6154 | 0.6667 | 0.64 | 0.9138 |
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- | No log | 11.0 | 77 | 0.5562 | 0.7692 | 0.8333 | 0.8 | 0.9483 |
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- | No log | 12.0 | 84 | 0.5408 | 0.7692 | 0.8333 | 0.8 | 0.9483 |
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- | No log | 13.0 | 91 | 0.8271 | 0.6667 | 0.6667 | 0.6667 | 0.9138 |
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- | No log | 14.0 | 98 | 1.5415 | 0.875 | 0.5833 | 0.7000 | 0.8793 |
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- | No log | 15.0 | 105 | 1.7072 | 0.8571 | 0.5 | 0.6316 | 0.8621 |
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- | No log | 16.0 | 112 | 1.7351 | 0.8571 | 0.5 | 0.6316 | 0.8621 |
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- | No log | 17.0 | 119 | 1.7483 | 0.8571 | 0.5 | 0.6316 | 0.8621 |
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- | No log | 18.0 | 126 | 1.1396 | 0.7273 | 0.6667 | 0.6957 | 0.8793 |
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- | No log | 19.0 | 133 | 0.7813 | 0.6667 | 0.6667 | 0.6667 | 0.8966 |
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- | No log | 20.0 | 140 | 0.5685 | 0.7692 | 0.8333 | 0.8 | 0.9310 |
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- | No log | 21.0 | 147 | 0.5689 | 0.7692 | 0.8333 | 0.8 | 0.9310 |
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- | No log | 22.0 | 154 | 1.0915 | 0.7273 | 0.6667 | 0.6957 | 0.8966 |
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- | No log | 23.0 | 161 | 0.6100 | 0.75 | 0.75 | 0.75 | 0.9310 |
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- | No log | 24.0 | 168 | 0.6199 | 0.7143 | 0.8333 | 0.7692 | 0.9138 |
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- | No log | 25.0 | 175 | 0.7130 | 0.7143 | 0.8333 | 0.7692 | 0.8966 |
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- | No log | 26.0 | 182 | 0.5825 | 0.7692 | 0.8333 | 0.8 | 0.9310 |
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- | No log | 27.0 | 189 | 0.5352 | 0.7692 | 0.8333 | 0.8 | 0.9310 |
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- | No log | 28.0 | 196 | 0.5182 | 0.7692 | 0.8333 | 0.8 | 0.9310 |
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- | No log | 29.0 | 203 | 0.5138 | 0.7692 | 0.8333 | 0.8 | 0.9310 |
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- | No log | 30.0 | 210 | 0.5142 | 0.7692 | 0.8333 | 0.8 | 0.9483 |
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- | No log | 31.0 | 217 | 0.5332 | 0.7692 | 0.8333 | 0.8 | 0.9483 |
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- | No log | 32.0 | 224 | 0.5501 | 0.7692 | 0.8333 | 0.8 | 0.9483 |
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- | No log | 33.0 | 231 | 0.5644 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 34.0 | 238 | 0.5722 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 35.0 | 245 | 0.5759 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 36.0 | 252 | 0.5776 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 37.0 | 259 | 0.5784 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 38.0 | 266 | 0.5788 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 39.0 | 273 | 0.5790 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 40.0 | 280 | 0.5786 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 41.0 | 287 | 0.5786 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 42.0 | 294 | 0.5787 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 43.0 | 301 | 0.5788 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 44.0 | 308 | 0.5790 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 45.0 | 315 | 0.6023 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 46.0 | 322 | 0.6284 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 47.0 | 329 | 0.6261 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 48.0 | 336 | 0.6254 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 49.0 | 343 | 0.6135 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 50.0 | 350 | 0.6077 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 51.0 | 357 | 0.6051 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 52.0 | 364 | 0.6041 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 53.0 | 371 | 0.6038 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 54.0 | 378 | 0.6034 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 55.0 | 385 | 0.6030 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 56.0 | 392 | 0.6030 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 57.0 | 399 | 0.6030 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 58.0 | 406 | 0.6024 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 59.0 | 413 | 0.6022 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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- | No log | 60.0 | 420 | 0.6021 | 0.6429 | 0.75 | 0.6923 | 0.9310 |
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  ### Framework versions
 
20
 
21
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
22
  It achieves the following results on the evaluation set:
23
+ - Loss: 0.2715
24
+ - Precision: 0.8333
25
+ - Recall: 0.8333
26
+ - F1: 0.8333
27
+ - Accuracy: 0.9483
28
 
29
  ## Model description
30
 
 
43
  ### Training hyperparameters
44
 
45
  The following hyperparameters were used during training:
46
+ - learning_rate: 2e-05
47
  - train_batch_size: 8
48
  - eval_batch_size: 8
49
  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
57
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 7 | 0.6895 | 0.0 | 0.0 | 0.0 | 0.7241 |
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+ | No log | 2.0 | 14 | 0.5915 | 0.0 | 0.0 | 0.0 | 0.7241 |
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+ | No log | 3.0 | 21 | 0.4062 | 0.2 | 0.0833 | 0.1176 | 0.7759 |
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+ | No log | 4.0 | 28 | 0.3063 | 0.5 | 0.5833 | 0.5385 | 0.8966 |
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+ | No log | 5.0 | 35 | 0.2520 | 0.5333 | 0.6667 | 0.5926 | 0.9138 |
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+ | No log | 6.0 | 42 | 0.2474 | 0.6667 | 0.6667 | 0.6667 | 0.9310 |
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+ | No log | 7.0 | 49 | 0.2140 | 0.6923 | 0.75 | 0.7200 | 0.9483 |
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+ | No log | 8.0 | 56 | 0.1894 | 0.8333 | 0.8333 | 0.8333 | 0.9655 |
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+ | No log | 9.0 | 63 | 0.1890 | 0.8333 | 0.8333 | 0.8333 | 0.9655 |
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+ | No log | 10.0 | 70 | 0.2119 | 0.8182 | 0.75 | 0.7826 | 0.9483 |
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+ | No log | 11.0 | 77 | 0.2343 | 0.8182 | 0.75 | 0.7826 | 0.9483 |
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+ | No log | 12.0 | 84 | 0.2421 | 0.8182 | 0.75 | 0.7826 | 0.9483 |
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+ | No log | 13.0 | 91 | 0.2379 | 0.8182 | 0.75 | 0.7826 | 0.9483 |
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+ | No log | 14.0 | 98 | 0.2362 | 0.8182 | 0.75 | 0.7826 | 0.9483 |
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+ | No log | 15.0 | 105 | 0.2357 | 0.8182 | 0.75 | 0.7826 | 0.9483 |
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+ | No log | 16.0 | 112 | 0.2370 | 0.8182 | 0.75 | 0.7826 | 0.9483 |
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+ | No log | 17.0 | 119 | 0.2383 | 0.8182 | 0.75 | 0.7826 | 0.9483 |
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+ | No log | 18.0 | 126 | 0.2400 | 0.8182 | 0.75 | 0.7826 | 0.9483 |
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+ | No log | 19.0 | 133 | 0.2424 | 0.8182 | 0.75 | 0.7826 | 0.9483 |
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+ | No log | 20.0 | 140 | 0.2444 | 0.8182 | 0.75 | 0.7826 | 0.9483 |
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+ | No log | 21.0 | 147 | 0.2461 | 0.8333 | 0.8333 | 0.8333 | 0.9655 |
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+ | No log | 22.0 | 154 | 0.2481 | 0.8333 | 0.8333 | 0.8333 | 0.9655 |
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+ | No log | 23.0 | 161 | 0.2422 | 0.8333 | 0.8333 | 0.8333 | 0.9655 |
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+ | No log | 24.0 | 168 | 0.2408 | 0.8333 | 0.8333 | 0.8333 | 0.9655 |
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+ | No log | 25.0 | 175 | 0.2418 | 0.8333 | 0.8333 | 0.8333 | 0.9655 |
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+ | No log | 26.0 | 182 | 0.2444 | 0.8333 | 0.8333 | 0.8333 | 0.9655 |
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+ | No log | 27.0 | 189 | 0.2477 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 28.0 | 196 | 0.2504 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 29.0 | 203 | 0.2527 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 30.0 | 210 | 0.2545 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 31.0 | 217 | 0.2561 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 32.0 | 224 | 0.2572 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 33.0 | 231 | 0.2584 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 34.0 | 238 | 0.2596 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 35.0 | 245 | 0.2606 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 36.0 | 252 | 0.2613 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 37.0 | 259 | 0.2621 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 38.0 | 266 | 0.2629 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 39.0 | 273 | 0.2638 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 40.0 | 280 | 0.2645 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 41.0 | 287 | 0.2652 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 42.0 | 294 | 0.2659 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
100
+ | No log | 43.0 | 301 | 0.2666 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 44.0 | 308 | 0.2672 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 45.0 | 315 | 0.2678 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 46.0 | 322 | 0.2683 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
104
+ | No log | 47.0 | 329 | 0.2686 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
105
+ | No log | 48.0 | 336 | 0.2689 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 49.0 | 343 | 0.2693 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
107
+ | No log | 50.0 | 350 | 0.2697 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
108
+ | No log | 51.0 | 357 | 0.2699 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 52.0 | 364 | 0.2702 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
110
+ | No log | 53.0 | 371 | 0.2705 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
111
+ | No log | 54.0 | 378 | 0.2708 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
112
+ | No log | 55.0 | 385 | 0.2710 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
113
+ | No log | 56.0 | 392 | 0.2711 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
114
+ | No log | 57.0 | 399 | 0.2713 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
115
+ | No log | 58.0 | 406 | 0.2714 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
116
+ | No log | 59.0 | 413 | 0.2715 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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+ | No log | 60.0 | 420 | 0.2715 | 0.8333 | 0.8333 | 0.8333 | 0.9483 |
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  ### Framework versions
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