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: 060524_epoch_2
results: []
060524_epoch_2
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: 0.6952
- Accuracy: 0.7437
- Precision: 0.7569
- Recall: 0.7437
- F1: 0.7404
- Ratio: 0.6134
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: 42
- 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 |
|---|---|---|---|---|---|---|---|---|
| 0.7924 | 0.1626 | 10 | 0.7754 | 0.7101 | 0.7233 | 0.7101 | 0.7057 | 0.3782 |
| 0.641 | 0.3252 | 20 | 0.8257 | 0.7227 | 0.7451 | 0.7227 | 0.7162 | 0.6513 |
| 0.8108 | 0.4878 | 30 | 0.7629 | 0.7563 | 0.7564 | 0.7563 | 0.7563 | 0.4916 |
| 0.736 | 0.6504 | 40 | 0.7167 | 0.7731 | 0.7751 | 0.7731 | 0.7727 | 0.4580 |
| 0.6973 | 0.8130 | 50 | 0.7419 | 0.7143 | 0.7448 | 0.7143 | 0.7051 | 0.6765 |
| 0.7981 | 0.9756 | 60 | 0.6962 | 0.7437 | 0.7569 | 0.7437 | 0.7404 | 0.6134 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1