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ER_new_context
tringuyen-uit/ER_new_context
ER_new_context 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
- t5
- Access
- Public
- Created
- May 28, 2024
- Updated
- May 28, 2024
- SHA
- 6b7ce489
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. -->
ER_new_context
This model is a fine-tuned version of VietAI/vit5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4057
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.2979 | 0.1 | 100 | 1.2437 |
| 1.1026 | 0.19 | 200 | 0.7365 |
| 0.7482 | 0.29 | 300 | 0.5781 |
| 0.6258 | 0.38 | 400 | 0.5159 |
| 0.5153 | 0.48 | 500 | 0.4504 |
| 0.4802 | 0.57 | 600 | 0.4455 |
| 0.4905 | 0.67 | 700 | 0.4059 |
| 0.382 | 0.76 | 800 | 0.4778 |
| 0.3728 | 0.86 | 900 | 0.3985 |
| 0.3274 | 0.96 | 1000 | 0.3982 |
| 0.3639 | 1.05 | 1100 | 0.4184 |
| 0.2881 | 1.15 | 1200 | 0.4454 |
| 0.3194 | 1.24 | 1300 | 0.3778 |
| 0.2695 | 1.34 | 1400 | 0.3957 |
| 0.2894 | 1.43 | 1500 | 0.4000 |
| 0.276 | 1.53 | 1600 | 0.3984 |
| 0.2325 | 1.62 | 1700 | 0.3627 |
| 0.2192 | 1.72 | 1800 | 0.3782 |
| 0.279 | 1.81 | 1900 | 0.4161 |
| 0.2636 | 1.91 | 2000 | 0.4026 |
| 0.2932 | 2.01 | 2100 | 0.3232 |
| 0.206 | 2.1 | 2200 | 0.3633 |
| 0.1865 | 2.2 | 2300 | 0.4019 |
| 0.1651 | 2.29 | 2400 | 0.4385 |
| 0.167 | 2.39 | 2500 | 0.4277 |
| 0.1705 | 2.48 | 2600 | 0.4083 |
| 0.2321 | 2.58 | 2700 | 0.3667 |
| 0.1912 | 2.67 | 2800 | 0.3772 |
| 0.192 | 2.77 | 2900 | 0.4032 |
| 0.1881 | 2.87 | 3000 | 0.4059 |
| 0.152 | 2.96 | 3100 | 0.4057 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Question Answering
- Library
- transformers
- Type
- t5
- License
- mit
- Created
- May 28, 2024
- Updated
- May 28, 2024