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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 +51 -51
  2. model.safetensors +1 -1
  3. runs/Feb29_07-40-31_9879f2213cb5/events.out.tfevents.1709192454.9879f2213cb5.492.4 +3 -0
  4. 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: 0.0907
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  - Precision: 0.4286
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  - Recall: 0.6
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  - F1: 0.5
@@ -55,56 +55,56 @@ 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 | 3 | 0.8542 | 0.0 | 0.0 | 0.0 | 0.6 |
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- | No log | 2.0 | 6 | 0.7877 | 0.0 | 0.0 | 0.0 | 0.6 |
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- | No log | 3.0 | 9 | 0.7607 | 0.0 | 0.0 | 0.0 | 0.68 |
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- | No log | 4.0 | 12 | 0.7105 | 0.0 | 0.0 | 0.0 | 0.8 |
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- | No log | 5.0 | 15 | 0.6518 | 0.0 | 0.0 | 0.0 | 0.8 |
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- | No log | 6.0 | 18 | 0.6048 | 0.0 | 0.0 | 0.0 | 0.8 |
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- | No log | 7.0 | 21 | 0.5669 | 0.0 | 0.0 | 0.0 | 0.8 |
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- | No log | 8.0 | 24 | 0.5373 | 0.0 | 0.0 | 0.0 | 0.8 |
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- | No log | 9.0 | 27 | 0.4927 | 0.0 | 0.0 | 0.0 | 0.8 |
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- | No log | 10.0 | 30 | 0.4489 | 0.0 | 0.0 | 0.0 | 0.8 |
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- | No log | 11.0 | 33 | 0.4046 | 0.0 | 0.0 | 0.0 | 0.8 |
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- | No log | 12.0 | 36 | 0.3475 | 0.0 | 0.0 | 0.0 | 0.8 |
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- | No log | 13.0 | 39 | 0.3017 | 0.0 | 0.0 | 0.0 | 0.8 |
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- | No log | 14.0 | 42 | 0.2578 | 0.0 | 0.0 | 0.0 | 0.8 |
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- | No log | 15.0 | 45 | 0.2259 | 0.25 | 0.4 | 0.3077 | 0.88 |
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- | No log | 16.0 | 48 | 0.2010 | 0.25 | 0.4 | 0.3077 | 0.88 |
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- | No log | 17.0 | 51 | 0.1781 | 0.25 | 0.4 | 0.3077 | 0.88 |
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- | No log | 18.0 | 54 | 0.1556 | 0.25 | 0.4 | 0.3077 | 0.88 |
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- | No log | 19.0 | 57 | 0.1379 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 20.0 | 60 | 0.1260 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 21.0 | 63 | 0.1190 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 22.0 | 66 | 0.1121 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 23.0 | 69 | 0.1090 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 24.0 | 72 | 0.1082 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 25.0 | 75 | 0.1081 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 26.0 | 78 | 0.1094 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 27.0 | 81 | 0.1107 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 28.0 | 84 | 0.1111 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 29.0 | 87 | 0.1098 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 30.0 | 90 | 0.1083 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 31.0 | 93 | 0.1066 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 32.0 | 96 | 0.1038 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 33.0 | 99 | 0.1012 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 34.0 | 102 | 0.1000 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 35.0 | 105 | 0.0985 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 36.0 | 108 | 0.0969 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 37.0 | 111 | 0.0954 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 38.0 | 114 | 0.0938 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 39.0 | 117 | 0.0933 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 40.0 | 120 | 0.0929 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 41.0 | 123 | 0.0919 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 42.0 | 126 | 0.0915 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 43.0 | 129 | 0.0912 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 44.0 | 132 | 0.0909 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 45.0 | 135 | 0.0908 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 46.0 | 138 | 0.0907 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 47.0 | 141 | 0.0908 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 48.0 | 144 | 0.0907 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 49.0 | 147 | 0.0907 | 0.4286 | 0.6 | 0.5 | 0.92 |
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- | No log | 50.0 | 150 | 0.0907 | 0.4286 | 0.6 | 0.5 | 0.92 |
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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: 0.1275
24
  - Precision: 0.4286
25
  - Recall: 0.6
26
  - F1: 0.5
 
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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 | 3 | 0.9367 | 0.0 | 0.0 | 0.0 | 0.68 |
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+ | No log | 2.0 | 6 | 0.8615 | 0.0 | 0.0 | 0.0 | 0.6 |
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+ | No log | 3.0 | 9 | 0.8433 | 0.0 | 0.0 | 0.0 | 0.6 |
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+ | No log | 4.0 | 12 | 0.8251 | 0.0 | 0.0 | 0.0 | 0.72 |
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+ | No log | 5.0 | 15 | 0.7768 | 0.0 | 0.0 | 0.0 | 0.72 |
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+ | No log | 6.0 | 18 | 0.7183 | 0.0 | 0.0 | 0.0 | 0.8 |
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+ | No log | 7.0 | 21 | 0.6669 | 0.0 | 0.0 | 0.0 | 0.8 |
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+ | No log | 8.0 | 24 | 0.6266 | 0.0 | 0.0 | 0.0 | 0.8 |
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+ | No log | 9.0 | 27 | 0.5842 | 0.0 | 0.0 | 0.0 | 0.8 |
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+ | No log | 10.0 | 30 | 0.5485 | 0.0 | 0.0 | 0.0 | 0.8 |
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+ | No log | 11.0 | 33 | 0.5111 | 0.0 | 0.0 | 0.0 | 0.8 |
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+ | No log | 12.0 | 36 | 0.4580 | 0.0 | 0.0 | 0.0 | 0.8 |
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+ | No log | 13.0 | 39 | 0.4110 | 0.0 | 0.0 | 0.0 | 0.8 |
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+ | No log | 14.0 | 42 | 0.3546 | 0.0 | 0.0 | 0.0 | 0.8 |
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+ | No log | 15.0 | 45 | 0.3081 | 0.0 | 0.0 | 0.0 | 0.8 |
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+ | No log | 16.0 | 48 | 0.2641 | 0.1111 | 0.2 | 0.1429 | 0.84 |
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+ | No log | 17.0 | 51 | 0.2270 | 0.25 | 0.4 | 0.3077 | 0.88 |
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+ | No log | 18.0 | 54 | 0.1943 | 0.25 | 0.4 | 0.3077 | 0.88 |
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+ | No log | 19.0 | 57 | 0.1708 | 0.25 | 0.4 | 0.3077 | 0.88 |
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+ | No log | 20.0 | 60 | 0.1586 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 21.0 | 63 | 0.1593 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 22.0 | 66 | 0.1617 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 23.0 | 69 | 0.1628 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 24.0 | 72 | 0.1643 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 25.0 | 75 | 0.1595 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 26.0 | 78 | 0.1534 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 27.0 | 81 | 0.1472 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 28.0 | 84 | 0.1422 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 29.0 | 87 | 0.1384 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 30.0 | 90 | 0.1359 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 31.0 | 93 | 0.1315 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 32.0 | 96 | 0.1274 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 33.0 | 99 | 0.1244 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 34.0 | 102 | 0.1233 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 35.0 | 105 | 0.1226 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 36.0 | 108 | 0.1220 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 37.0 | 111 | 0.1220 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 38.0 | 114 | 0.1215 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 39.0 | 117 | 0.1219 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 40.0 | 120 | 0.1229 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 41.0 | 123 | 0.1239 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 42.0 | 126 | 0.1249 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 43.0 | 129 | 0.1255 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 44.0 | 132 | 0.1257 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 45.0 | 135 | 0.1261 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 46.0 | 138 | 0.1267 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 47.0 | 141 | 0.1271 | 0.4286 | 0.6 | 0.5 | 0.92 |
105
+ | No log | 48.0 | 144 | 0.1273 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 49.0 | 147 | 0.1275 | 0.4286 | 0.6 | 0.5 | 0.92 |
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+ | No log | 50.0 | 150 | 0.1275 | 0.4286 | 0.6 | 0.5 | 0.92 |
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  ### Framework versions
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