| | --- |
| | base_model: airesearch/wangchanberta-base-att-spm-uncased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: wisesight_sentiment |
| | 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. --> |
| |
|
| | # wisesight_sentiment |
| | |
| | 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: 0.4140 |
| | - Accuracy: 0.9025 |
| | - F1 Micro: 0.9025 |
| | - Precision Micro: 0.9025 |
| | - Recall Micro: 0.9025 |
| | - F1 Macro: 0.9010 |
| | - Precision Macro: 0.9006 |
| | - Recall Macro: 0.9015 |
| | - Nb Samples: 1015 |
| | |
| | ## 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: 3e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 1412 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 2031 |
| | - num_epochs: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Micro | Precision Micro | Recall Micro | F1 Macro | Precision Macro | Recall Macro | Nb Samples | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:----------:| |
| | | 0.587 | 1.0 | 2031 | 0.5865 | 0.8532 | 0.8532 | 0.8532 | 0.8532 | 0.8492 | 0.8550 | 0.8460 | 1015 | |
| | | 0.5212 | 2.0 | 4062 | 0.7026 | 0.8158 | 0.8158 | 0.8158 | 0.8158 | 0.8156 | 0.8380 | 0.8322 | 1015 | |
| | | 0.4554 | 3.0 | 6093 | 0.4360 | 0.8768 | 0.8768 | 0.8768 | 0.8768 | 0.8731 | 0.8813 | 0.8690 | 1015 | |
| | | 0.3752 | 4.0 | 8124 | 0.4121 | 0.8897 | 0.8897 | 0.8897 | 0.8897 | 0.8867 | 0.8929 | 0.8831 | 1015 | |
| | | 0.382 | 5.0 | 10155 | 0.4709 | 0.8916 | 0.8916 | 0.8916 | 0.8916 | 0.8894 | 0.8917 | 0.8876 | 1015 | |
| | | 0.3465 | 6.0 | 12186 | 0.3929 | 0.8975 | 0.8975 | 0.8975 | 0.8975 | 0.8957 | 0.8964 | 0.8952 | 1015 | |
| | | 0.3246 | 7.0 | 14217 | 0.4801 | 0.8897 | 0.8897 | 0.8897 | 0.8897 | 0.8873 | 0.8899 | 0.8854 | 1015 | |
| | | 0.2808 | 8.0 | 16248 | 0.5070 | 0.8897 | 0.8897 | 0.8897 | 0.8897 | 0.8881 | 0.8874 | 0.8889 | 1015 | |
| | | 0.2786 | 9.0 | 18279 | 0.4098 | 0.8995 | 0.8995 | 0.8995 | 0.8995 | 0.8975 | 0.8993 | 0.8962 | 1015 | |
| | | 0.2151 | 10.0 | 20310 | 0.4140 | 0.9025 | 0.9025 | 0.9025 | 0.9025 | 0.9010 | 0.9006 | 0.9015 | 1015 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.42.4 |
| | - Pytorch 2.3.1+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| |
|
