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distilbert_finetune_own_data_model

Token Classification
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distilbert
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  1. README.md +34 -34
  2. model.safetensors +1 -1
  3. runs/Mar04_12-04-47_561d3d140928/events.out.tfevents.1709553891.561d3d140928.17019.12 +3 -0
  4. runs/Mar04_12-04-47_561d3d140928/events.out.tfevents.1709553906.561d3d140928.17019.13 +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: 0.0324
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- - Precision: 0.9091
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  - Recall: 1.0
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- - F1: 0.9524
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- - Accuracy: 0.9825
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  ## Model description
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@@ -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 | 0.5691 | 0.0 | 0.0 | 0.0 | 0.7895 |
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- | No log | 2.0 | 16 | 0.4212 | 0.0 | 0.0 | 0.0 | 0.7895 |
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- | No log | 3.0 | 24 | 0.2519 | 0.8333 | 0.5 | 0.625 | 0.8772 |
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- | No log | 4.0 | 32 | 0.1510 | 0.6154 | 0.8 | 0.6957 | 0.9474 |
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- | No log | 5.0 | 40 | 0.1091 | 0.6667 | 0.8 | 0.7273 | 0.9649 |
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- | No log | 6.0 | 48 | 0.0739 | 0.75 | 0.9 | 0.8182 | 0.9649 |
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- | No log | 7.0 | 56 | 0.0542 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 8.0 | 64 | 0.0398 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 9.0 | 72 | 0.0289 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 10.0 | 80 | 0.0285 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 11.0 | 88 | 0.0320 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 12.0 | 96 | 0.0333 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 13.0 | 104 | 0.0327 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 14.0 | 112 | 0.0319 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 15.0 | 120 | 0.0315 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 16.0 | 128 | 0.0312 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 17.0 | 136 | 0.0310 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 18.0 | 144 | 0.0302 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 19.0 | 152 | 0.0302 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 20.0 | 160 | 0.0307 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 21.0 | 168 | 0.0311 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 22.0 | 176 | 0.0313 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 23.0 | 184 | 0.0314 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 24.0 | 192 | 0.0315 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 25.0 | 200 | 0.0317 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 26.0 | 208 | 0.0320 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 27.0 | 216 | 0.0322 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 28.0 | 224 | 0.0323 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 29.0 | 232 | 0.0323 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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- | No log | 30.0 | 240 | 0.0324 | 0.9091 | 1.0 | 0.9524 | 0.9825 |
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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: 0.0342
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+ - Precision: 0.9286
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  - Recall: 1.0
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+ - F1: 0.9630
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+ - Accuracy: 0.9851
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  ## Model description
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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 | 10 | 0.5163 | 0.0 | 0.0 | 0.0 | 0.7910 |
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+ | No log | 2.0 | 20 | 0.3270 | 1.0 | 0.2308 | 0.375 | 0.8358 |
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+ | No log | 3.0 | 30 | 0.1767 | 0.7692 | 0.7692 | 0.7692 | 0.9403 |
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+ | No log | 4.0 | 40 | 0.0969 | 0.8 | 0.9231 | 0.8571 | 0.9701 |
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+ | No log | 5.0 | 50 | 0.0688 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 6.0 | 60 | 0.0484 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 7.0 | 70 | 0.0379 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 8.0 | 80 | 0.0376 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 9.0 | 90 | 0.0304 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 10.0 | 100 | 0.0271 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 11.0 | 110 | 0.0224 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 12.0 | 120 | 0.0212 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 13.0 | 130 | 0.0257 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 14.0 | 140 | 0.0301 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 15.0 | 150 | 0.0311 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 16.0 | 160 | 0.0309 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 17.0 | 170 | 0.0305 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 18.0 | 180 | 0.0302 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 19.0 | 190 | 0.0301 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 20.0 | 200 | 0.0301 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 21.0 | 210 | 0.0303 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 22.0 | 220 | 0.0305 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 23.0 | 230 | 0.0308 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 24.0 | 240 | 0.0309 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 25.0 | 250 | 0.0323 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 26.0 | 260 | 0.0336 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 27.0 | 270 | 0.0340 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 28.0 | 280 | 0.0341 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 29.0 | 290 | 0.0342 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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+ | No log | 30.0 | 300 | 0.0342 | 0.9286 | 1.0 | 0.9630 | 0.9851 |
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  ### Framework versions
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