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--- |
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library_name: transformers |
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license: mit |
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base_model: vinai/phobert-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: phobert-human-tl-seed-6969 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# phobert-human-tl-seed-6969 |
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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: 0.4535 |
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- Accuracy: 0.8387 |
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- Precision: 0.6438 |
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- Recall: 0.4677 |
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- F1: 0.4914 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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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: 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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 50 |
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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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| No log | 1.0 | 346 | 0.5154 | 0.8241 | 0.5456 | 0.3492 | 0.3314 | |
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| 0.5778 | 2.0 | 692 | 0.4712 | 0.8305 | 0.6220 | 0.4062 | 0.4191 | |
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| 0.4667 | 3.0 | 1038 | 0.4650 | 0.8331 | 0.6490 | 0.4069 | 0.4227 | |
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| 0.4667 | 4.0 | 1384 | 0.4665 | 0.8365 | 0.6819 | 0.4147 | 0.4337 | |
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| 0.4617 | 5.0 | 1730 | 0.4639 | 0.8357 | 0.6591 | 0.4129 | 0.4337 | |
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| 0.4577 | 6.0 | 2076 | 0.4606 | 0.8368 | 0.6775 | 0.4282 | 0.4479 | |
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| 0.4577 | 7.0 | 2422 | 0.4626 | 0.8361 | 0.6851 | 0.4134 | 0.4359 | |
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| 0.4554 | 8.0 | 2768 | 0.4530 | 0.8394 | 0.6468 | 0.4436 | 0.4674 | |
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| 0.4545 | 9.0 | 3114 | 0.4599 | 0.8342 | 0.6459 | 0.4083 | 0.4288 | |
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| 0.4545 | 10.0 | 3460 | 0.4603 | 0.8350 | 0.6825 | 0.4375 | 0.4543 | |
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| 0.4587 | 11.0 | 3806 | 0.4594 | 0.8346 | 0.6499 | 0.4092 | 0.4321 | |
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| 0.4491 | 12.0 | 4152 | 0.4535 | 0.8387 | 0.6438 | 0.4677 | 0.4914 | |
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| 0.4491 | 13.0 | 4498 | 0.4555 | 0.8353 | 0.6372 | 0.4213 | 0.4475 | |
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| 0.4579 | 14.0 | 4844 | 0.4563 | 0.8357 | 0.6552 | 0.4129 | 0.4359 | |
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| 0.4488 | 15.0 | 5190 | 0.4595 | 0.8335 | 0.6553 | 0.4019 | 0.4217 | |
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| 0.4587 | 16.0 | 5536 | 0.4663 | 0.8327 | 0.6580 | 0.3987 | 0.4161 | |
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| 0.4587 | 17.0 | 5882 | 0.4515 | 0.8387 | 0.6235 | 0.4357 | 0.4612 | |
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### Framework versions |
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- Transformers 4.51.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.0 |
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