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---
license: cc-by-4.0
base_model: strongpear/deberta-large_vMCQ
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-large_vMCQ
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. -->
# deberta-large_vMCQ
This model is a fine-tuned version of [strongpear/deberta-large_vMCQ](https://huggingface.co/strongpear/deberta-large_vMCQ) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3767
- Accuracy: 0.9097
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3415 | 0.08 | 500 | 0.3459 | 0.9033 |
| 0.299 | 0.17 | 1000 | 0.5000 | 0.8988 |
| 0.3761 | 0.25 | 1500 | 0.4322 | 0.8994 |
| 0.3655 | 0.33 | 2000 | 0.4337 | 0.8990 |
| 0.3576 | 0.42 | 2500 | 0.4655 | 0.9027 |
| 0.3178 | 0.5 | 3000 | 0.4377 | 0.9046 |
| 0.3789 | 0.58 | 3500 | 0.4241 | 0.9072 |
| 0.32 | 0.67 | 4000 | 0.3855 | 0.9074 |
| 0.3655 | 0.75 | 4500 | 0.3848 | 0.9076 |
| 0.3426 | 0.83 | 5000 | 0.3931 | 0.9072 |
| 0.356 | 0.91 | 5500 | 0.3797 | 0.9089 |
| 0.3965 | 1.0 | 6000 | 0.3767 | 0.9097 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1
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