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funa21
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phobert-finetuned-vsmec

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End of training

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  1. README.md +9 -9
  2. logs/events.out.tfevents.1740234760.funa.34795.0 +2 -2
  3. model.safetensors +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1147
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- - Accuracy: 0.6093
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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: 32
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- - eval_batch_size: 32
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.7036 | 1.0 | 174 | 1.3638 | 0.5335 |
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- | 1.2578 | 2.0 | 348 | 1.1908 | 0.5598 |
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- | 1.0045 | 3.0 | 522 | 1.1279 | 0.5845 |
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- | 0.8574 | 4.0 | 696 | 1.1230 | 0.5962 |
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- | 0.7932 | 5.0 | 870 | 1.1147 | 0.6093 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1522
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+ - Accuracy: 0.5991
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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: 16
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+ - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.6546 | 1.0 | 347 | 1.2939 | 0.5350 |
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+ | 1.1657 | 2.0 | 694 | 1.2315 | 0.5481 |
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+ | 0.8851 | 3.0 | 1041 | 1.1145 | 0.5904 |
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+ | 0.7219 | 4.0 | 1388 | 1.1473 | 0.5918 |
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+ | 0.6244 | 5.0 | 1735 | 1.1522 | 0.5991 |
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  ### Framework versions
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