metadata
license: apache-2.0
base_model: projecte-aina/roberta-base-ca-v2-cased-te
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 2504separado3
results: []
2504separado3
This model is a fine-tuned version of projecte-aina/roberta-base-ca-v2-cased-te on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6752
- Accuracy: 0.8445
- Precision: 0.8451
- Recall: 0.8445
- F1: 0.8445
- Ratio: 0.5210
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 4
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Ratio |
|---|---|---|---|---|---|---|---|---|
| 0.404 | 0.9870 | 38 | 0.7068 | 0.8151 | 0.8174 | 0.8151 | 0.8148 | 0.5420 |
| 0.3648 | 2.0 | 77 | 0.6934 | 0.8277 | 0.8317 | 0.8277 | 0.8272 | 0.5546 |
| 0.3989 | 2.9870 | 115 | 0.6752 | 0.8445 | 0.8451 | 0.8445 | 0.8445 | 0.5210 |
| 0.4125 | 3.9481 | 152 | 0.6799 | 0.8361 | 0.8367 | 0.8361 | 0.8361 | 0.5210 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1