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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 +25 -35
  2. model.safetensors +1 -1
  3. runs/Mar05_05-45-20_fbd7a420be06/events.out.tfevents.1709617537.fbd7a420be06.558.2 +3 -0
  4. runs/Mar05_05-47-55_fbd7a420be06/events.out.tfevents.1709617687.fbd7a420be06.558.3 +3 -0
  5. runs/Mar05_05-47-55_fbd7a420be06/events.out.tfevents.1709618151.fbd7a420be06.558.4 +3 -0
  6. 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: 0.0403
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- - Precision: 0.9412
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  - Recall: 1.0
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- - F1: 0.9697
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- - Accuracy: 0.9873
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  ## Model description
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@@ -49,42 +49,32 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 30
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  ### Training results
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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 | 13 | 0.5817 | 0.0 | 0.0 | 0.0 | 0.7722 |
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- | No log | 2.0 | 26 | 0.3957 | 0.0 | 0.0 | 0.0 | 0.7848 |
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- | No log | 3.0 | 39 | 0.2136 | 0.6875 | 0.6875 | 0.6875 | 0.9241 |
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- | No log | 4.0 | 52 | 0.1080 | 0.7368 | 0.875 | 0.8000 | 0.9620 |
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- | No log | 5.0 | 65 | 0.0854 | 0.8125 | 0.8125 | 0.8125 | 0.9494 |
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- | No log | 6.0 | 78 | 0.0526 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 7.0 | 91 | 0.0411 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 8.0 | 104 | 0.0388 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 9.0 | 117 | 0.0332 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 10.0 | 130 | 0.0323 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 11.0 | 143 | 0.0364 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 12.0 | 156 | 0.0378 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 13.0 | 169 | 0.0370 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 14.0 | 182 | 0.0371 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 15.0 | 195 | 0.0374 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 16.0 | 208 | 0.0383 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 17.0 | 221 | 0.0397 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 18.0 | 234 | 0.0398 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 19.0 | 247 | 0.0400 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 20.0 | 260 | 0.0399 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 21.0 | 273 | 0.0397 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 22.0 | 286 | 0.0398 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 23.0 | 299 | 0.0399 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 24.0 | 312 | 0.0400 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 25.0 | 325 | 0.0401 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 26.0 | 338 | 0.0401 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 27.0 | 351 | 0.0402 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 28.0 | 364 | 0.0402 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 29.0 | 377 | 0.0403 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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- | No log | 30.0 | 390 | 0.0403 | 0.9412 | 1.0 | 0.9697 | 0.9873 |
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  ### Framework versions
 
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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: 0.0011
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+ - Precision: 1.0
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  - Recall: 1.0
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+ - F1: 1.0
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+ - Accuracy: 1.0
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 20
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  ### Training results
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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 | 14 | 0.5130 | 0.0 | 0.0 | 0.0 | 0.7722 |
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+ | No log | 2.0 | 28 | 0.2590 | 0.7143 | 0.625 | 0.6667 | 0.9241 |
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+ | No log | 3.0 | 42 | 0.1134 | 0.7647 | 0.8125 | 0.7879 | 0.9620 |
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+ | No log | 4.0 | 56 | 0.0633 | 0.7778 | 0.875 | 0.8235 | 0.9747 |
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+ | No log | 5.0 | 70 | 0.0343 | 0.7778 | 0.875 | 0.8235 | 0.9747 |
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+ | No log | 6.0 | 84 | 0.0133 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 7.0 | 98 | 0.0071 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 8.0 | 112 | 0.0041 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 9.0 | 126 | 0.0030 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 10.0 | 140 | 0.0024 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 11.0 | 154 | 0.0020 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 12.0 | 168 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 13.0 | 182 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 14.0 | 196 | 0.0014 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 15.0 | 210 | 0.0013 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 16.0 | 224 | 0.0012 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 17.0 | 238 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 18.0 | 252 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 19.0 | 266 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 20.0 | 280 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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