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checkpoints_1_18
Rzoro/checkpoints_1_18
checkpoints_1_18 is a multiple choice model from Rzoro. Use it for the multiple choice task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- multiple choice
- Library
- transformers
- Model type
- deberta-v2
- Access
- Public
- Created
- Sep 16, 2023
- Updated
- Sep 25, 2023
- SHA
- 041d8e59
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. -->
checkpoints_1_18
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0029
- Map@3: 0.7167
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: 1
- eval_batch_size: 1
- seed: 0
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Map@3 |
|---|---|---|---|---|
| 1.142 | 0.11 | 500 | 1.0493 | 0.7237 |
| 0.9838 | 0.21 | 1000 | 1.0372 | 0.7165 |
| 0.9986 | 0.32 | 1500 | 1.3068 | 0.6970 |
| 1.0107 | 0.42 | 2000 | 1.1471 | 0.7107 |
| 1.0236 | 0.53 | 2500 | 1.1068 | 0.7115 |
| 1.0616 | 0.63 | 3000 | 1.0636 | 0.7170 |
| 1.1416 | 0.74 | 3500 | 1.0426 | 0.7183 |
| 1.1879 | 0.84 | 4000 | 1.0135 | 0.7147 |
| 1.2246 | 0.95 | 4500 | 1.0029 | 0.7167 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- multiple choice
- Library
- transformers
- Type
- deberta-v2
- Created
- Sep 16, 2023
- Updated
- Sep 25, 2023