| --- |
| base_model: airesearch/wangchanberta-base-att-spm-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: ESG_Sentiment_Prediction |
| 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. --> |
|
|
| # ESG_Sentiment_Prediction |
|
|
| 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: 0.6823 |
| - Accuracy: 0.6851 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
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|
| More information needed |
|
|
| ## Training and evaluation data |
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|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 1e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 391 | 0.7735 | 0.6312 | |
| | 0.757 | 2.0 | 782 | 0.7041 | 0.6567 | |
| | 0.688 | 3.0 | 1173 | 0.7295 | 0.6298 | |
| | 0.6327 | 4.0 | 1564 | 0.6858 | 0.6837 | |
| | 0.6327 | 5.0 | 1955 | 0.6823 | 0.6851 | |
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| ### Framework versions |
|
|
| - Transformers 4.37.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.1 |
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|
