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bert-small-finetuned-finetuned

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  1. README.md +23 -23
  2. model.safetensors +1 -1
  3. runs/Nov09_12-57-03_41f8e8250b9c/events.out.tfevents.1699534623.41f8e8250b9c.518.10 +2 -2
  4. runs/Nov09_12-57-03_41f8e8250b9c/events.out.tfevents.1699535200.41f8e8250b9c.518.11 +3 -0
README.md CHANGED
@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ryantaw/bert-small-finetuned](https://huggingface.co/ryantaw/bert-small-finetuned) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6962
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- - Accuracy: 0.7358
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- - F1 Score: 0.7334
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  ## Model description
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@@ -50,26 +50,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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- | No log | 1.0 | 18 | 0.6962 | 0.7358 | 0.7334 |
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- | No log | 2.0 | 36 | 0.7131 | 0.7197 | 0.7187 |
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- | No log | 3.0 | 54 | 0.7094 | 0.7170 | 0.7171 |
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- | No log | 4.0 | 72 | 0.7098 | 0.7170 | 0.7160 |
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- | No log | 5.0 | 90 | 0.7446 | 0.7143 | 0.7120 |
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- | No log | 6.0 | 108 | 0.7464 | 0.7008 | 0.6986 |
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- | No log | 7.0 | 126 | 0.7771 | 0.6981 | 0.6912 |
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- | No log | 8.0 | 144 | 0.7748 | 0.7008 | 0.7005 |
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- | No log | 9.0 | 162 | 0.7806 | 0.7197 | 0.7209 |
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- | No log | 10.0 | 180 | 0.7835 | 0.7089 | 0.7061 |
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- | No log | 11.0 | 198 | 0.8341 | 0.7035 | 0.6970 |
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- | No log | 12.0 | 216 | 0.8166 | 0.7116 | 0.7122 |
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- | No log | 13.0 | 234 | 0.8369 | 0.7062 | 0.7053 |
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- | No log | 14.0 | 252 | 0.8367 | 0.7008 | 0.6982 |
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- | No log | 15.0 | 270 | 0.9065 | 0.6846 | 0.6783 |
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- | No log | 16.0 | 288 | 0.8928 | 0.6873 | 0.6851 |
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- | No log | 17.0 | 306 | 0.8936 | 0.6900 | 0.6870 |
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- | No log | 18.0 | 324 | 0.8881 | 0.6981 | 0.6960 |
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- | No log | 19.0 | 342 | 0.8974 | 0.6819 | 0.6789 |
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- | No log | 20.0 | 360 | 0.8964 | 0.6819 | 0.6784 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [ryantaw/bert-small-finetuned](https://huggingface.co/ryantaw/bert-small-finetuned) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0767
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+ - Accuracy: 0.6119
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+ - F1 Score: 0.6156
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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+ | 0.7125 | 1.0 | 18 | 1.0136 | 0.6011 | 0.5997 |
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+ | 0.604 | 2.0 | 36 | 1.0198 | 0.6038 | 0.6058 |
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+ | 0.5421 | 3.0 | 54 | 1.0517 | 0.6065 | 0.6068 |
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+ | 0.4724 | 4.0 | 72 | 1.0767 | 0.6119 | 0.6156 |
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+ | 0.42 | 5.0 | 90 | 1.1184 | 0.5768 | 0.5751 |
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+ | 0.3823 | 6.0 | 108 | 1.1217 | 0.5876 | 0.5881 |
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+ | 0.3312 | 7.0 | 126 | 1.1425 | 0.6065 | 0.6053 |
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+ | 0.3045 | 8.0 | 144 | 1.1760 | 0.6065 | 0.6095 |
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+ | 0.2662 | 9.0 | 162 | 1.2044 | 0.6065 | 0.6090 |
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+ | 0.2403 | 10.0 | 180 | 1.2143 | 0.6011 | 0.6011 |
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+ | 0.2308 | 11.0 | 198 | 1.2394 | 0.5903 | 0.5927 |
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+ | 0.2053 | 12.0 | 216 | 1.2589 | 0.6038 | 0.6068 |
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+ | 0.1808 | 13.0 | 234 | 1.2895 | 0.6065 | 0.6071 |
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+ | 0.1599 | 14.0 | 252 | 1.3144 | 0.6065 | 0.6086 |
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+ | 0.1497 | 15.0 | 270 | 1.3386 | 0.5930 | 0.5951 |
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+ | 0.1383 | 16.0 | 288 | 1.3608 | 0.5903 | 0.5931 |
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+ | 0.1321 | 17.0 | 306 | 1.3624 | 0.5876 | 0.5888 |
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+ | 0.1183 | 18.0 | 324 | 1.3810 | 0.5930 | 0.5945 |
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+ | 0.1196 | 19.0 | 342 | 1.3827 | 0.5903 | 0.5927 |
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+ | 0.1181 | 20.0 | 360 | 1.3805 | 0.5903 | 0.5920 |
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  ### Framework versions
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