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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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- f1 |
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model-index: |
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- name: metadata-cls-no-gov-8k-v3 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/nguyenducbao/huggingface/runs/gi7dm5g5) |
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# metadata-cls-no-gov-8k-v3 |
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This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3064 |
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- Accuracy: 0.9515 |
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- F1: 0.8155 |
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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: 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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:| |
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| 0.5565 | 1.6393 | 200 | 0.1942 | 0.9472 | 0.7911 | |
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| 0.1619 | 3.2787 | 400 | 0.1935 | 0.9404 | 0.7817 | |
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| 0.1275 | 4.9180 | 600 | 0.1903 | 0.9430 | 0.8019 | |
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| 0.0768 | 6.5574 | 800 | 0.2192 | 0.9489 | 0.8016 | |
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| 0.0579 | 8.1967 | 1000 | 0.2350 | 0.9455 | 0.7866 | |
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| 0.0477 | 9.8361 | 1200 | 0.2572 | 0.9498 | 0.7952 | |
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| 0.0358 | 11.4754 | 1400 | 0.2823 | 0.9413 | 0.7938 | |
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| 0.0277 | 13.1148 | 1600 | 0.2704 | 0.9464 | 0.8096 | |
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| 0.0233 | 14.7541 | 1800 | 0.2868 | 0.9481 | 0.7951 | |
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| 0.0139 | 16.3934 | 2000 | 0.3026 | 0.9438 | 0.7965 | |
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| 0.0125 | 18.0328 | 2200 | 0.3034 | 0.9489 | 0.8035 | |
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| 0.0085 | 19.6721 | 2400 | 0.3064 | 0.9515 | 0.8155 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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