metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
datasets:
- told-br
model-index:
- name: iag-class-ptbr
results: []
iag-class-ptbr
This model is a fine-tuned version of roberta-base on the told-br dataset. It achieves the following results on the evaluation set:
- Loss: 0.5147
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: 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 |
|---|---|---|---|
| 0.5936 | 1.0 | 2100 | 0.5406 |
| 0.4858 | 2.0 | 4200 | 0.5394 |
| 0.5622 | 3.0 | 6300 | 0.5147 |
| 0.4538 | 4.0 | 8400 | 0.5310 |
| 0.4305 | 5.0 | 10500 | 0.5799 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3