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: 0.0650
- F1: 0.9786
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 |
|---|---|---|---|---|
| 0.5298 | 1.0 | 46 | 0.5474 | 0.6476 |
| 0.4054 | 2.0 | 92 | 0.3447 | 0.8075 |
| 0.1121 | 3.0 | 138 | 0.2614 | 0.8747 |
| 0.3135 | 4.0 | 184 | 0.1970 | 0.9132 |
| 0.2817 | 5.0 | 230 | 0.1525 | 0.9331 |
| 0.1796 | 6.0 | 276 | 0.1200 | 0.9470 |
| 0.0267 | 7.0 | 322 | 0.0967 | 0.9631 |
| 0.1953 | 8.0 | 368 | 0.0829 | 0.9691 |
| 0.0168 | 9.0 | 414 | 0.0746 | 0.9754 |
| 0.0858 | 10.0 | 460 | 0.0650 | 0.9786 |
Framework versions
- Transformers 4.28.1
- Pytorch 1.13.1
- Datasets 2.12.0
- Tokenizers 0.13.3