Model save
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README.md
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---
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base_model: vinai/phobert-base-v2
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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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model-index:
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- name: model
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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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# model
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This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3215
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- Accuracy: 0.9594
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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: 2e-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: 10
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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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| No log | 1.0 | 122 | 2.0600 | 0.5594 |
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| No log | 2.0 | 244 | 1.3525 | 0.7844 |
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| No log | 3.0 | 366 | 0.9400 | 0.8812 |
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| No log | 4.0 | 488 | 0.6653 | 0.9344 |
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| 1.295 | 5.0 | 610 | 0.5045 | 0.9469 |
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| 1.295 | 6.0 | 732 | 0.4192 | 0.9594 |
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| 1.295 | 7.0 | 854 | 0.3692 | 0.9563 |
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| 1.295 | 8.0 | 976 | 0.3445 | 0.9563 |
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| 0.2942 | 9.0 | 1098 | 0.3258 | 0.9563 |
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| 0.2942 | 10.0 | 1220 | 0.3215 | 0.9594 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu118
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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model.safetensors
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