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roberta-mc-2
bimoadiparwa/roberta-mc-2
roberta-mc-2 is a multiple choice model from bimoadiparwa. 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. 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
- multiple choice
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Aug 15, 2023
- Updated
- Aug 15, 2023
- SHA
- 29c4cfaf
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. -->
roberta-mc-2
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5972
- Accuracy: 0.4
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: 5e-06
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.6096 | 1.0 | 24 | 1.6086 | 0.3 |
| 1.614 | 2.0 | 48 | 1.6083 | 0.4 |
| 1.6032 | 3.0 | 72 | 1.6070 | 0.4 |
| 1.6185 | 4.0 | 96 | 1.6057 | 0.4 |
| 1.6106 | 5.0 | 120 | 1.6045 | 0.4 |
| 1.6093 | 6.0 | 144 | 1.6028 | 0.4 |
| 1.597 | 7.0 | 168 | 1.6010 | 0.4 |
| 1.6094 | 8.0 | 192 | 1.5994 | 0.4 |
| 1.6029 | 9.0 | 216 | 1.5977 | 0.4 |
| 1.5997 | 10.0 | 240 | 1.5972 | 0.4 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- multiple choice
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Aug 15, 2023
- Updated
- Aug 15, 2023