metadata
library_name: transformers
license: mit
base_model: belisards/congretimbau
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: modelos
results: []
modelos
This model is a fine-tuned version of belisards/congretimbau on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5239
- Accuracy: 0.8254
- F1: 0.7442
- Recall: 0.7267
- Precision: 0.7727
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 5151
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 0.5681 | 1.0323 | 32 | 0.5508 | 0.75 | 0.4286 | 0.5 | 0.375 |
| 0.5233 | 2.0645 | 64 | 0.5138 | 0.7381 | 0.5146 | 0.5317 | 0.5897 |
| 0.4339 | 3.0968 | 96 | 0.4529 | 0.7917 | 0.6875 | 0.6706 | 0.7240 |
| 0.3907 | 4.1290 | 128 | 0.4087 | 0.8393 | 0.7683 | 0.75 | 0.7970 |
| 0.2166 | 5.1613 | 160 | 0.4054 | 0.8452 | 0.7867 | 0.7778 | 0.7976 |
| 0.14 | 6.1935 | 192 | 0.4474 | 0.8274 | 0.7716 | 0.7738 | 0.7696 |
| 0.0673 | 7.2258 | 224 | 0.5118 | 0.8393 | 0.7726 | 0.7579 | 0.7932 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1