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curse_classification

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djsull/curse_classification

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  1. README.md +9 -12
  2. model.safetensors +1 -1
  3. runs/Dec16_08-51-55_129-146-79-76/events.out.tfevents.1734339116.129-146-79-76.3971573.0 +3 -0
  4. runs/Dec16_08-51-55_129-146-79-76/events.out.tfevents.1734339969.129-146-79-76.3971573.1 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2877
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- - Precision: 0.8475
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- - Recall: 0.8934
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- - F1: 0.8698
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- - Accuracy: 0.8767
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 64
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  - eval_batch_size: 64
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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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.3204 | 1.0 | 1235 | 0.3171 | 0.7810 | 0.9095 | 0.8403 | 0.8469 |
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- | 0.239 | 2.0 | 2470 | 0.2997 | 0.8361 | 0.8802 | 0.8576 | 0.8704 |
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- | 0.1616 | 3.0 | 3705 | 0.3649 | 0.8201 | 0.8917 | 0.8544 | 0.8653 |
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- | 0.0996 | 4.0 | 4940 | 0.4684 | 0.8389 | 0.8707 | 0.8545 | 0.8686 |
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- | 0.0654 | 5.0 | 6175 | 0.5530 | 0.8611 | 0.8532 | 0.8571 | 0.8740 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2780
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+ - Precision: 0.8727
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+ - Recall: 0.8752
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+ - F1: 0.8739
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+ - Accuracy: 0.8835
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 128
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  - eval_batch_size: 64
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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: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.3511 | 1.0 | 618 | 0.2939 | 0.8532 | 0.8591 | 0.8561 | 0.8720 |
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+ | 0.2546 | 2.0 | 1236 | 0.2924 | 0.8721 | 0.8552 | 0.8636 | 0.8802 |
 
 
 
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  ### Framework versions
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