license: mit | |
base_model: xlm-roberta-base | |
tags: | |
- generated_from_trainer | |
metrics: | |
- accuracy | |
- precision | |
- recall | |
model-index: | |
- name: xlm-roberta-base-finetuned-detests-wandb24 | |
results: [] | |
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# xlm-roberta-base-finetuned-detests-wandb24 | |
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.4371 | |
- Accuracy: 0.7938 | |
- F1-score: 0.7241 | |
- Precision: 0.7136 | |
- Recall: 0.7396 | |
- Auc: 0.7396 | |
## 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: 5e-05 | |
- train_batch_size: 16 | |
- eval_batch_size: 16 | |
- seed: 42 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- num_epochs: 2 | |
### Training results | |
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall | Auc | | |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:| | |
| 0.458 | 1.0 | 153 | 0.4512 | 0.7725 | 0.4358 | 0.3863 | 0.5 | 0.5 | | |
| 0.4262 | 2.0 | 306 | 0.4371 | 0.7938 | 0.7241 | 0.7136 | 0.7396 | 0.7396 | | |
### Framework versions | |
- Transformers 4.37.2 | |
- Pytorch 2.1.0+cu121 | |
- Datasets 2.17.0 | |
- Tokenizers 0.15.1 | |