---
license: cc-by-4.0
base_model: deepset/deberta-v3-large-squad2
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 [deepset/deberta-v3-large-squad2](https://huggingface.co/deepset/deberta-v3-large-squad2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3480
- Accuracy: 0.9061

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5525        | 0.17  | 1000 | 0.4781          | 0.8777   |
| 0.4107        | 0.33  | 2000 | 0.3763          | 0.8924   |
| 0.3733        | 0.5   | 3000 | 0.3605          | 0.8967   |
| 0.39          | 0.67  | 4000 | 0.3378          | 0.9050   |
| 0.3674        | 0.83  | 5000 | 0.3407          | 0.9053   |
| 0.3507        | 1.0   | 6000 | 0.3480          | 0.9061   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1