metadata
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: DIPROMATS_subtask_1_base_train
results: []
DIPROMATS_subtask_1_base_train
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5120
- F1: 0.8267
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: 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.4533 | 1.0 | 182 | 0.3471 | 0.7932 |
| 0.1763 | 2.0 | 364 | 0.3473 | 0.8116 |
| 0.1359 | 3.0 | 546 | 0.3887 | 0.8144 |
| 0.1728 | 4.0 | 728 | 0.4311 | 0.8147 |
| 0.1519 | 5.0 | 910 | 0.4881 | 0.8236 |
| 0.0085 | 6.0 | 1092 | 0.5120 | 0.8267 |
| 0.1828 | 7.0 | 1274 | 0.5591 | 0.8118 |
| 0.0071 | 8.0 | 1456 | 0.6079 | 0.8263 |
| 0.0015 | 9.0 | 1638 | 0.6919 | 0.8235 |
| 0.0241 | 10.0 | 1820 | 0.6990 | 0.8221 |
Framework versions
- Transformers 4.28.1
- Pytorch 1.13.1
- Datasets 2.12.0
- Tokenizers 0.13.3