| | --- |
| | license: mit |
| | base_model: FacebookAI/xlm-roberta-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: roberta-finetuned-inspirational |
| | 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. --> |
| |
|
| | # roberta-finetuned-inspirational |
| |
|
| | This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1617 |
| | - F1: 0.9683 |
| | - Roc Auc: 0.9622 |
| | - Accuracy: 0.9125 |
| |
|
| | ## 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 |
| | - num_epochs: 5 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
| | | 0.312 | 1.0 | 600 | 0.2784 | 0.9053 | 0.8878 | 0.7333 | |
| | | 0.1656 | 2.0 | 1200 | 0.1670 | 0.9468 | 0.9348 | 0.8542 | |
| | | 0.0967 | 3.0 | 1800 | 0.1803 | 0.9585 | 0.9504 | 0.8865 | |
| | | 0.0685 | 4.0 | 2400 | 0.1694 | 0.9639 | 0.9568 | 0.9021 | |
| | | 0.0286 | 5.0 | 3000 | 0.1617 | 0.9683 | 0.9622 | 0.9125 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.39.3 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| |
|
