| --- |
| base_model: airesearch/wangchanberta-base-att-spm-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: lst20-sent-segment |
| 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. --> |
|
|
| # lst20-sent-segment |
|
|
| This model is a fine-tuned version of [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1513 |
| - Precision: 0.7125 |
| - Recall: 0.5426 |
| - F1: 0.6160 |
| - Accuracy: 0.9403 |
|
|
| ## 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: 1e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.1842 | 1.0 | 1274 | 0.1596 | 0.6990 | 0.4995 | 0.5827 | 0.9361 | |
| | 0.1622 | 2.0 | 2548 | 0.1513 | 0.7052 | 0.5330 | 0.6071 | 0.9389 | |
| | 0.1554 | 3.0 | 3822 | 0.1513 | 0.7125 | 0.5426 | 0.6160 | 0.9403 | |
|
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|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.15.0 |
| - Tokenizers 0.15.0 |
|
|
