metadata
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: refine-good-name-xlm-roberta
results: []
refine-good-name-xlm-roberta
This model is a fine-tuned version of xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2236
- F1: 0.8688
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.2618 | 1.0 | 553 | 0.2357 | 0.8314 |
| 0.2025 | 2.0 | 1106 | 0.2209 | 0.8661 |
| 0.186 | 3.0 | 1659 | 0.2075 | 0.8588 |
| 0.162 | 4.0 | 2212 | 0.2234 | 0.8609 |
| 0.1428 | 5.0 | 2765 | 0.2233 | 0.8700 |
| 0.1328 | 6.0 | 3318 | 0.2236 | 0.8688 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.0
- Datasets 2.14.0
- Tokenizers 0.13.3