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: 080524_epoch_13
results: []
080524_epoch_13
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: 0.8371
- Accuracy: 0.8151
- Precision: 0.8509
- Recall: 0.8151
- F1: 0.8103
- Ratio: 0.6597
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: 10
- eval_batch_size: 2
- seed: 47
- gradient_accumulation_steps: 2
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- lr_scheduler_warmup_steps: 4
- num_epochs: 1
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Ratio |
|---|---|---|---|---|---|---|---|---|
| 0.3002 | 0.1176 | 10 | 0.8662 | 0.8151 | 0.8509 | 0.8151 | 0.8103 | 0.6597 |
| 0.3026 | 0.2353 | 20 | 0.7930 | 0.8277 | 0.8516 | 0.8277 | 0.8248 | 0.6303 |
| 0.2933 | 0.3529 | 30 | 0.7946 | 0.8277 | 0.8484 | 0.8277 | 0.8251 | 0.6218 |
| 0.2921 | 0.4706 | 40 | 0.8687 | 0.8151 | 0.8509 | 0.8151 | 0.8103 | 0.6597 |
| 0.2947 | 0.5882 | 50 | 0.8540 | 0.8109 | 0.8442 | 0.8109 | 0.8062 | 0.6555 |
| 0.3148 | 0.7059 | 60 | 0.8454 | 0.8151 | 0.8469 | 0.8151 | 0.8108 | 0.6513 |
| 0.3221 | 0.8235 | 70 | 0.8642 | 0.8151 | 0.8509 | 0.8151 | 0.8103 | 0.6597 |
| 0.316 | 0.9412 | 80 | 0.8389 | 0.8151 | 0.8509 | 0.8151 | 0.8103 | 0.6597 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1