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akbarsigit
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mental_classification

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distilbert
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End of training

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  2. model.safetensors +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/distilbert-base-uncased](https://huggingface.co/distilbert/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: 0.5913
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- - Accuracy: 0.8815
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  ## Model description
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@@ -43,21 +43,21 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 15
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-------:|:----:|:---------------:|:--------:|
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- | 2.2665 | 1.5038 | 197 | 1.6089 | 0.5908 |
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- | 1.1385 | 3.0076 | 394 | 1.0268 | 0.7610 |
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- | 0.5896 | 4.5115 | 591 | 0.7455 | 0.8394 |
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- | 0.3186 | 6.0153 | 788 | 0.6275 | 0.8566 |
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- | 0.1691 | 7.5191 | 985 | 0.5975 | 0.8719 |
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- | 0.0971 | 9.0229 | 1182 | 0.5844 | 0.8623 |
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- | 0.0597 | 10.5267 | 1379 | 0.5824 | 0.8757 |
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- | 0.0418 | 12.0305 | 1576 | 0.5894 | 0.8776 |
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- | 0.0334 | 13.5344 | 1773 | 0.5913 | 0.8815 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/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: 0.6424
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+ - Accuracy: 0.8623
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 14
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | 2.356 | 1.4046 | 184 | 1.6835 | 0.5908 |
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+ | 1.2119 | 2.8092 | 368 | 1.1011 | 0.7648 |
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+ | 0.6548 | 4.2137 | 552 | 0.8192 | 0.8241 |
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+ | 0.3782 | 5.6183 | 736 | 0.6968 | 0.8375 |
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+ | 0.1931 | 7.0229 | 920 | 0.6587 | 0.8528 |
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+ | 0.1127 | 8.4275 | 1104 | 0.6390 | 0.8566 |
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+ | 0.081 | 9.8321 | 1288 | 0.6382 | 0.8566 |
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+ | 0.0532 | 11.2366 | 1472 | 0.6433 | 0.8623 |
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+ | 0.0416 | 12.6412 | 1656 | 0.6424 | 0.8623 |
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  ### Framework versions
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