metadata
license: apache-2.0
base_model: projecte-aina/roberta-base-ca-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fm-tc-authentic
results: []
fm-tc-authentic
This model is a fine-tuned version of projecte-aina/roberta-base-ca-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2183
- Accuracy: 0.684
- Precision: 0.4290
- Recall: 0.4443
- F1: 0.4224
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 2.2298 | 1.0 | 568 | 1.5513 | 0.576 | 0.2101 | 0.2781 | 0.2186 |
| 1.4142 | 2.0 | 1136 | 1.2728 | 0.652 | 0.3275 | 0.3903 | 0.3517 |
| 1.1276 | 3.0 | 1704 | 1.2183 | 0.684 | 0.4290 | 0.4443 | 0.4224 |
| 0.8384 | 4.0 | 2272 | 1.2388 | 0.672 | 0.5085 | 0.4718 | 0.4609 |
| 0.6867 | 5.0 | 2840 | 1.2870 | 0.674 | 0.5075 | 0.4686 | 0.4597 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1