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tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-mc-3
results: []
---
<!-- 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-3
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5988
- Accuracy: 0.3
## 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-07
- 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: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6111 | 1.0 | 24 | 1.6061 | 0.4 |
| 1.6003 | 2.0 | 48 | 1.6062 | 0.4 |
| 1.6049 | 3.0 | 72 | 1.6062 | 0.4 |
| 1.5936 | 4.0 | 96 | 1.6059 | 0.4 |
| 1.6073 | 5.0 | 120 | 1.6057 | 0.4 |
| 1.6001 | 6.0 | 144 | 1.6055 | 0.3 |
| 1.5925 | 7.0 | 168 | 1.6052 | 0.3 |
| 1.5971 | 8.0 | 192 | 1.6050 | 0.3 |
| 1.597 | 9.0 | 216 | 1.6047 | 0.3 |
| 1.5956 | 10.0 | 240 | 1.6042 | 0.3 |
| 1.5882 | 11.0 | 264 | 1.6036 | 0.3 |
| 1.5944 | 12.0 | 288 | 1.6034 | 0.3 |
| 1.5941 | 13.0 | 312 | 1.6032 | 0.3 |
| 1.5941 | 14.0 | 336 | 1.6029 | 0.3 |
| 1.5825 | 15.0 | 360 | 1.6024 | 0.3 |
| 1.5817 | 16.0 | 384 | 1.6019 | 0.3 |
| 1.5922 | 17.0 | 408 | 1.6014 | 0.3 |
| 1.5915 | 18.0 | 432 | 1.6011 | 0.3 |
| 1.5822 | 19.0 | 456 | 1.6007 | 0.3 |
| 1.5967 | 20.0 | 480 | 1.6001 | 0.3 |
| 1.5887 | 21.0 | 504 | 1.5999 | 0.3 |
| 1.5905 | 22.0 | 528 | 1.5997 | 0.3 |
| 1.5828 | 23.0 | 552 | 1.5994 | 0.3 |
| 1.5851 | 24.0 | 576 | 1.5992 | 0.3 |
| 1.5789 | 25.0 | 600 | 1.5991 | 0.3 |
| 1.5797 | 26.0 | 624 | 1.5990 | 0.3 |
| 1.5845 | 27.0 | 648 | 1.5989 | 0.3 |
| 1.5992 | 28.0 | 672 | 1.5988 | 0.3 |
| 1.5791 | 29.0 | 696 | 1.5988 | 0.3 |
| 1.5785 | 30.0 | 720 | 1.5988 | 0.3 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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