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: output
results: []
output
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: 1.2062
- Accuracy: 0.674
- Precision: 0.3364
- Recall: 0.4130
- F1: 0.3663
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 |
|---|---|---|---|---|---|---|---|
| 2.2715 | 1.0 | 568 | 1.6059 | 0.558 | 0.2024 | 0.2319 | 0.1918 |
| 1.4728 | 2.0 | 1136 | 1.2854 | 0.644 | 0.3297 | 0.3636 | 0.3367 |
| 1.1552 | 3.0 | 1704 | 1.2062 | 0.674 | 0.3364 | 0.4130 | 0.3663 |
| 0.8737 | 4.0 | 2272 | 1.2907 | 0.662 | 0.4354 | 0.4474 | 0.4240 |
| 0.7023 | 5.0 | 2840 | 1.3429 | 0.658 | 0.4609 | 0.4661 | 0.4461 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1