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distilbert_finetune_own_data_model

Token Classification
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Safetensors
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_10-27-45_561d3d140928/events.out.tfevents.1709548092.561d3d140928.17019.2 +3 -0
  4. runs/Mar04_10-27-45_561d3d140928/events.out.tfevents.1709548106.561d3d140928.17019.3 +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: 0.0210
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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 | 6 | 0.6845 | 0.0 | 0.0 | 0.0 | 0.7317 |
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- | No log | 2.0 | 12 | 0.5401 | 0.0 | 0.0 | 0.0 | 0.7317 |
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- | No log | 3.0 | 18 | 0.3678 | 0.6667 | 0.3636 | 0.4706 | 0.8293 |
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- | No log | 4.0 | 24 | 0.2400 | 0.8 | 0.7273 | 0.7619 | 0.9268 |
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- | No log | 5.0 | 30 | 0.1767 | 0.8 | 0.7273 | 0.7619 | 0.9268 |
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- | No log | 6.0 | 36 | 0.1407 | 0.8182 | 0.8182 | 0.8182 | 0.9512 |
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- | No log | 7.0 | 42 | 0.1167 | 0.8182 | 0.8182 | 0.8182 | 0.9512 |
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- | No log | 8.0 | 48 | 0.1017 | 1.0 | 0.9091 | 0.9524 | 0.9756 |
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- | No log | 9.0 | 54 | 0.0812 | 1.0 | 0.9091 | 0.9524 | 0.9756 |
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- | No log | 10.0 | 60 | 0.0628 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 11.0 | 66 | 0.0508 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 12.0 | 72 | 0.0435 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 13.0 | 78 | 0.0388 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 14.0 | 84 | 0.0354 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 15.0 | 90 | 0.0325 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 16.0 | 96 | 0.0302 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 17.0 | 102 | 0.0285 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 18.0 | 108 | 0.0289 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 19.0 | 114 | 0.0284 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 20.0 | 120 | 0.0272 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 21.0 | 126 | 0.0259 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 22.0 | 132 | 0.0248 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 23.0 | 138 | 0.0237 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 24.0 | 144 | 0.0229 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 25.0 | 150 | 0.0222 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 26.0 | 156 | 0.0217 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 27.0 | 162 | 0.0213 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 28.0 | 168 | 0.0211 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 29.0 | 174 | 0.0210 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 30.0 | 180 | 0.0210 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
 
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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:
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+ - Loss: 0.0381
24
  - Precision: 1.0
25
  - Recall: 1.0
26
  - 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 | 6 | 0.7417 | 0.0 | 0.0 | 0.0 | 0.6905 |
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+ | No log | 2.0 | 12 | 0.6341 | 0.0 | 0.0 | 0.0 | 0.6905 |
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+ | No log | 3.0 | 18 | 0.4825 | 0.3333 | 0.0909 | 0.1429 | 0.7381 |
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+ | No log | 4.0 | 24 | 0.3477 | 0.5714 | 0.3636 | 0.4444 | 0.8095 |
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+ | No log | 5.0 | 30 | 0.2585 | 0.6 | 0.5455 | 0.5714 | 0.8810 |
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+ | No log | 6.0 | 36 | 0.2038 | 0.6364 | 0.6364 | 0.6364 | 0.9048 |
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+ | No log | 7.0 | 42 | 0.1639 | 1.0 | 0.8182 | 0.9 | 0.9524 |
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+ | No log | 8.0 | 48 | 0.1359 | 1.0 | 0.8182 | 0.9 | 0.9524 |
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+ | No log | 9.0 | 54 | 0.1067 | 1.0 | 0.8182 | 0.9 | 0.9524 |
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+ | No log | 10.0 | 60 | 0.0870 | 1.0 | 0.9091 | 0.9524 | 0.9762 |
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+ | No log | 11.0 | 66 | 0.0736 | 1.0 | 0.9091 | 0.9524 | 0.9762 |
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+ | No log | 12.0 | 72 | 0.0645 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 13.0 | 78 | 0.0580 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 14.0 | 84 | 0.0534 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 15.0 | 90 | 0.0500 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 16.0 | 96 | 0.0474 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 17.0 | 102 | 0.0454 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 18.0 | 108 | 0.0432 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 19.0 | 114 | 0.0418 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 20.0 | 120 | 0.0409 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 21.0 | 126 | 0.0403 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 22.0 | 132 | 0.0399 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 23.0 | 138 | 0.0394 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 24.0 | 144 | 0.0390 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 25.0 | 150 | 0.0387 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 26.0 | 156 | 0.0385 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 27.0 | 162 | 0.0383 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 28.0 | 168 | 0.0382 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 29.0 | 174 | 0.0381 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 30.0 | 180 | 0.0381 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
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