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MRC_ER_InfoXLM-large_syl_DSC
tringuyen-uit/MRC_ER_InfoXLM-large_syl_DSC
MRC_ER_InfoXLM-large_syl_DSC 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Sep 4, 2024
- Updated
- Sep 5, 2024
- SHA
- d14890b8
Try a prompt
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_InfoXLM-large_syl_DSC
This model is a fine-tuned version of tringuyen-uit/MRC_ER_InfoXLM-large_syl_DSC on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9789
- Exact Match: 0.7016
- F1: 0.8574
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
|---|---|---|---|---|---|
| 0.6848 | 1.0 | 12728 | 0.9842 | 0.6596 | 0.8277 |
| 0.6025 | 2.0 | 25456 | 0.9789 | 0.7016 | 0.8574 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Question Answering
- Library
- transformers
- Type
- xlm-roberta
- Created
- Sep 4, 2024
- Updated
- Sep 5, 2024