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MRC_ER_XLM-base_syl_ViWikiFC
tringuyen-uit/MRC_ER_XLM-base_syl_ViWikiFC
MRC_ER_XLM-base_syl_ViWikiFC is a question answering model from tringuyen-uit. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jun 13, 2024
- Updated
- Jun 13, 2024
- SHA
- 61e7c892
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
MRC_ER_XLM-base_syl_ViWikiFC
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4375
- Exact Match: 0.8010
- F1: 0.8260
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 |
|---|---|---|---|---|---|
| 0.5246 | 1.0 | 2093 | 1.9799 | 0.7751 | 0.8080 |
| 0.4175 | 2.0 | 4186 | 1.9344 | 0.7856 | 0.8126 |
| 0.3522 | 3.0 | 6279 | 2.0761 | 0.7981 | 0.8274 |
| 0.2593 | 4.0 | 8372 | 2.3028 | 0.7990 | 0.8225 |
| 0.1676 | 5.0 | 10465 | 2.4375 | 0.8010 | 0.8260 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
- Task
- Question Answering
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jun 13, 2024
- Updated
- Jun 13, 2024