metadata
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: clarifier-good-name-xlm-roberta
results: []
clarifier-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: 0.3007
- F1: 0.8746
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.2794 | 1.0 | 553 | 0.2373 | 0.8460 |
| 0.208 | 2.0 | 1106 | 0.2176 | 0.8585 |
| 0.1915 | 3.0 | 1659 | 0.2057 | 0.8542 |
| 0.1662 | 4.0 | 2212 | 0.2216 | 0.8635 |
| 0.1472 | 5.0 | 2765 | 0.2160 | 0.8709 |
| 0.132 | 6.0 | 3318 | 0.2297 | 0.8703 |
| 0.1255 | 7.0 | 3871 | 0.2617 | 0.8709 |
| 0.1162 | 8.0 | 4424 | 0.2973 | 0.8738 |
| 0.1036 | 9.0 | 4977 | 0.2818 | 0.8713 |
| 0.1 | 10.0 | 5530 | 0.3007 | 0.8746 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.0
- Datasets 2.14.0
- Tokenizers 0.13.3