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youngbreadho
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distilbert-base-uncased-distilled-clinc

Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
Inference Endpoints
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Training complete

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  1. README.md +12 -12
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1634
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- - Accuracy: 0.9442
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  ## Model description
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@@ -49,16 +49,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.4474 | 1.0 | 318 | 0.9228 | 0.7145 |
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- | 0.7092 | 2.0 | 636 | 0.4341 | 0.8623 |
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- | 0.3679 | 3.0 | 954 | 0.2540 | 0.92 |
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- | 0.2374 | 4.0 | 1272 | 0.2006 | 0.9355 |
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- | 0.1905 | 5.0 | 1590 | 0.1837 | 0.9397 |
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- | 0.1708 | 6.0 | 1908 | 0.1737 | 0.9445 |
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- | 0.1601 | 7.0 | 2226 | 0.1691 | 0.9410 |
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- | 0.154 | 8.0 | 2544 | 0.1656 | 0.9442 |
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- | 0.1503 | 9.0 | 2862 | 0.1638 | 0.9448 |
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- | 0.1483 | 10.0 | 3180 | 0.1634 | 0.9442 |
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1160
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+ - Accuracy: 0.9419
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.1786 | 1.0 | 318 | 0.7011 | 0.7113 |
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+ | 0.5333 | 2.0 | 636 | 0.3054 | 0.8581 |
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+ | 0.2694 | 3.0 | 954 | 0.1794 | 0.9187 |
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+ | 0.1792 | 4.0 | 1272 | 0.1441 | 0.9313 |
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+ | 0.1468 | 5.0 | 1590 | 0.1316 | 0.9358 |
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+ | 0.1323 | 6.0 | 1908 | 0.1242 | 0.9406 |
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+ | 0.1239 | 7.0 | 2226 | 0.1207 | 0.9381 |
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+ | 0.1189 | 8.0 | 2544 | 0.1179 | 0.9406 |
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+ | 0.116 | 9.0 | 2862 | 0.1163 | 0.9426 |
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+ | 0.1143 | 10.0 | 3180 | 0.1160 | 0.9419 |
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  ### Framework versions
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