| | --- |
| | license: mit |
| | base_model: LIAMF-USP/roberta-large-finetuned-race |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | model-index: |
| | - name: test-roberta-finetuned-mathqa |
| | 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. --> |
| |
|
| | # test-roberta-finetuned-mathqa |
| |
|
| | This model is a fine-tuned version of [LIAMF-USP/roberta-large-finetuned-race](https://huggingface.co/LIAMF-USP/roberta-large-finetuned-race) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.6094 |
| | - Accuracy: 0.2007 |
| | - F1: 0.1089 |
| | - Precision: 0.1782 |
| | - Recall: 0.1954 |
| |
|
| | ## 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: 10 |
| | - 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 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | | 1.6207 | 1.0 | 2970 | 1.6094 | 0.2064 | 0.0714 | 0.1694 | 0.2010 | |
| | | 1.6136 | 2.0 | 5940 | 1.6094 | 0.2064 | 0.0951 | 0.1934 | 0.2020 | |
| | | 1.6161 | 3.0 | 8910 | 1.6094 | 0.2007 | 0.1089 | 0.1782 | 0.1954 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.40.2 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.19.1 |
| | - Tokenizers 0.19.1 |
| |
|
