| | --- |
| | license: mit |
| | base_model: xlm-roberta-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: fine_tuned_cb_XLMroberta |
| | 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. --> |
| |
|
| | # fine_tuned_cb_XLMroberta |
| | |
| | This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.4876 |
| | - Accuracy: 0.6364 |
| | - F1: 0.5977 |
| | |
| | ## 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: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - training_steps: 400 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:| |
| | | 0.8279 | 3.5714 | 50 | 1.1428 | 0.3182 | 0.1536 | |
| | | 0.6981 | 7.1429 | 100 | 1.2578 | 0.3182 | 0.1536 | |
| | | 0.6005 | 10.7143 | 150 | 1.2018 | 0.3636 | 0.2430 | |
| | | 0.2959 | 14.2857 | 200 | 1.1990 | 0.6364 | 0.5916 | |
| | | 0.1743 | 17.8571 | 250 | 1.5253 | 0.5909 | 0.5562 | |
| | | 0.1206 | 21.4286 | 300 | 1.8099 | 0.5 | 0.4423 | |
| | | 0.0357 | 25.0 | 350 | 1.7105 | 0.5909 | 0.5545 | |
| | | 0.0189 | 28.5714 | 400 | 1.4876 | 0.6364 | 0.5977 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.40.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.19.1 |
| | - Tokenizers 0.19.1 |
| | |
