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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 +31 -31
  2. model.safetensors +1 -1
  3. runs/Mar04_11-23-43_561d3d140928/events.out.tfevents.1709551435.561d3d140928.17019.6 +3 -0
  4. runs/Mar04_11-23-43_561d3d140928/events.out.tfevents.1709551449.561d3d140928.17019.7 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -20,7 +20,7 @@ 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: 0.0199
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  - Precision: 1.0
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  - Recall: 1.0
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  - F1: 1.0
@@ -55,36 +55,36 @@ 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 | 8 | 0.6810 | 0.0 | 0.0 | 0.0 | 0.72 |
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- | No log | 2.0 | 16 | 0.5830 | 0.0 | 0.0 | 0.0 | 0.72 |
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- | No log | 3.0 | 24 | 0.3702 | 0.4 | 0.1667 | 0.2353 | 0.78 |
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- | No log | 4.0 | 32 | 0.2550 | 0.6 | 0.5 | 0.5455 | 0.88 |
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- | No log | 5.0 | 40 | 0.1929 | 0.6667 | 0.6667 | 0.6667 | 0.92 |
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- | No log | 6.0 | 48 | 0.1598 | 0.6667 | 0.6667 | 0.6667 | 0.92 |
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- | No log | 7.0 | 56 | 0.1300 | 1.0 | 0.8333 | 0.9091 | 0.96 |
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- | No log | 8.0 | 64 | 0.0927 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 9.0 | 72 | 0.0712 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 10.0 | 80 | 0.0561 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 11.0 | 88 | 0.0475 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 12.0 | 96 | 0.0429 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 13.0 | 104 | 0.0363 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 14.0 | 112 | 0.0333 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 15.0 | 120 | 0.0316 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 16.0 | 128 | 0.0291 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 17.0 | 136 | 0.0270 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 18.0 | 144 | 0.0255 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 19.0 | 152 | 0.0244 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 20.0 | 160 | 0.0235 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 21.0 | 168 | 0.0228 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 22.0 | 176 | 0.0222 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 23.0 | 184 | 0.0219 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 24.0 | 192 | 0.0214 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 25.0 | 200 | 0.0210 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 26.0 | 208 | 0.0207 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 27.0 | 216 | 0.0203 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 28.0 | 224 | 0.0201 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 29.0 | 232 | 0.0200 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 30.0 | 240 | 0.0199 | 1.0 | 1.0 | 1.0 | 1.0 |
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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: 0.0315
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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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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 8 | 0.6792 | 0.0 | 0.0 | 0.0 | 0.72 |
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+ | No log | 2.0 | 16 | 0.5792 | 0.0 | 0.0 | 0.0 | 0.72 |
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+ | No log | 3.0 | 24 | 0.3634 | 0.4 | 0.1667 | 0.2353 | 0.78 |
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+ | No log | 4.0 | 32 | 0.2497 | 0.6364 | 0.5833 | 0.6087 | 0.9 |
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+ | No log | 5.0 | 40 | 0.1926 | 0.6667 | 0.6667 | 0.6667 | 0.92 |
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+ | No log | 6.0 | 48 | 0.1531 | 0.8182 | 0.75 | 0.7826 | 0.94 |
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+ | No log | 7.0 | 56 | 0.1200 | 1.0 | 0.8333 | 0.9091 | 0.96 |
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+ | No log | 8.0 | 64 | 0.0861 | 1.0 | 0.9167 | 0.9565 | 0.98 |
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+ | No log | 9.0 | 72 | 0.0685 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 10.0 | 80 | 0.0617 | 1.0 | 0.8333 | 0.9091 | 0.96 |
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+ | No log | 11.0 | 88 | 0.0548 | 1.0 | 0.8333 | 0.9091 | 0.96 |
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+ | No log | 12.0 | 96 | 0.0506 | 1.0 | 0.8333 | 0.9091 | 0.96 |
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+ | No log | 13.0 | 104 | 0.0476 | 1.0 | 0.9167 | 0.9565 | 0.98 |
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+ | No log | 14.0 | 112 | 0.0445 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 15.0 | 120 | 0.0409 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 16.0 | 128 | 0.0383 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 17.0 | 136 | 0.0367 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 18.0 | 144 | 0.0357 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 19.0 | 152 | 0.0344 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 20.0 | 160 | 0.0338 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 21.0 | 168 | 0.0333 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 22.0 | 176 | 0.0332 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 23.0 | 184 | 0.0331 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 24.0 | 192 | 0.0327 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 25.0 | 200 | 0.0326 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 26.0 | 208 | 0.0322 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 27.0 | 216 | 0.0318 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 28.0 | 224 | 0.0317 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 29.0 | 232 | 0.0315 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 30.0 | 240 | 0.0315 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
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