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mrc-videberta-base-dsc
MiuN2k3/mrc-videberta-base-dsc
mrc-videberta-base-dsc is a question answering model from MiuN2k3. 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
- deberta-v2
- Access
- Public
- Created
- May 29, 2024
- Updated
- May 29, 2024
- SHA
- 84e49433
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-videnerta-dsc
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: 0.8100
- Exact Match: 0.5970
- F1: 0.7653
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 |
|---|---|---|---|---|---|
| 0.967 | 1.0 | 3098 | 0.8918 | 0.5358 | 0.7128 |
| 0.8396 | 2.0 | 6196 | 0.8346 | 0.5610 | 0.7488 |
| 0.7209 | 3.0 | 9294 | 0.8057 | 0.5825 | 0.7624 |
| 0.6532 | 4.0 | 12392 | 0.8212 | 0.5951 | 0.7513 |
| 0.601 | 5.0 | 15490 | 0.8100 | 0.5970 | 0.7653 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.2.1
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Question Answering
- Library
- transformers
- Type
- deberta-v2
- Created
- May 29, 2024
- Updated
- May 29, 2024