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starclass_bert

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  1. README.md +12 -10
  2. logs/events.out.tfevents.1737435754.PC +2 -2
  3. model.safetensors +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3155
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- - Accuracy: 0.9524
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- - Precision: 0.9542
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- - Recall: 0.9524
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- - F1: 0.9529
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  ## Model description
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  ### Training hyperparameters
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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: 16
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  - eval_batch_size: 16
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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: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 1.2284 | 1.0 | 16 | 0.7756 | 0.7619 | 0.7900 | 0.7619 | 0.7351 |
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- | 0.5657 | 2.0 | 32 | 0.4658 | 0.9206 | 0.9235 | 0.9206 | 0.9207 |
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- | 0.4123 | 3.0 | 48 | 0.3155 | 0.9524 | 0.9542 | 0.9524 | 0.9529 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3450
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+ - Accuracy: 0.9206
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+ - Precision: 0.9242
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+ - Recall: 0.9206
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+ - F1: 0.9202
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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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 | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 1.2965 | 1.0 | 16 | 1.0060 | 0.6190 | 0.7989 | 0.6190 | 0.5413 |
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+ | 0.8967 | 2.0 | 32 | 0.7731 | 0.8571 | 0.9005 | 0.8571 | 0.8556 |
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+ | 0.6978 | 3.0 | 48 | 0.5247 | 0.9365 | 0.9382 | 0.9365 | 0.9364 |
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+ | 0.4319 | 4.0 | 64 | 0.3859 | 0.9365 | 0.9382 | 0.9365 | 0.9364 |
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+ | 0.3069 | 5.0 | 80 | 0.3450 | 0.9206 | 0.9242 | 0.9206 | 0.9202 |
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  ### Framework versions
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