MRC_ER_videberta-base_word_ViWikiFC
This model is a fine-tuned version of Fsoft-AIC/videberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.0166
- Exact Match: 0.7804
- F1: 0.8093
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
|---|---|---|---|---|---|
| 0.6374 | 1.0 | 2093 | 1.7652 | 0.7622 | 0.7962 |
| 0.5612 | 2.0 | 4186 | 1.7521 | 0.7718 | 0.8046 |
| 0.5021 | 3.0 | 6279 | 1.8670 | 0.7823 | 0.8110 |
| 0.4184 | 4.0 | 8372 | 1.9411 | 0.7823 | 0.8087 |
| 0.381 | 5.0 | 10465 | 2.0166 | 0.7804 | 0.8093 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for tringuyen-uit/MRC_ER_videberta-base_word_ViWikiFC
Base model
Fsoft-AIC/videberta-base