metadata
license: apache-2.0
base_model: BSC-TeMU/roberta-base-bne
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: roberta-base-bne-finetuned-detests-wandb24
results: []
roberta-base-bne-finetuned-detests-wandb24
This model is a fine-tuned version of BSC-TeMU/roberta-base-bne on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4065
- Accuracy: 0.8527
- F1-score: 0.7826
- Precision: 0.7945
- Recall: 0.7727
- Auc: 0.7727
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|---|---|---|---|
| 0.3296 | 1.0 | 77 | 0.3456 | 0.8543 | 0.7671 | 0.8142 | 0.7408 | 0.7408 |
| 0.1555 | 2.0 | 154 | 0.4065 | 0.8527 | 0.7826 | 0.7945 | 0.7727 | 0.7727 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1