| | --- |
| | base_model: gechim/metadata-cls-no-gov-8k-v3 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: PhobertLexicalMeta |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | [<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/h3pap4wy) |
| | # PhobertLexicalMeta |
| |
|
| | This model is a fine-tuned version of [gechim/metadata-cls-no-gov-8k-v3](https://huggingface.co/gechim/metadata-cls-no-gov-8k-v3) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0927 |
| | - Accuracy: 0.9792 |
| | - F1: 0.9664 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 2e-05 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
| | | 0.1701 | 1.9608 | 200 | 0.0936 | 0.9741 | 0.9575 | |
| | | 0.0537 | 3.9216 | 400 | 0.0780 | 0.9780 | 0.9647 | |
| | | 0.0252 | 5.8824 | 600 | 0.0762 | 0.9805 | 0.9687 | |
| | | 0.016 | 7.8431 | 800 | 0.0996 | 0.9780 | 0.9640 | |
| | | 0.0098 | 9.8039 | 1000 | 0.0927 | 0.9792 | 0.9664 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.43.1 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| |
|
