pytorch tensorboard deberta-v2 fill-mask transformers generated_from_trainer license:mit model-index autotrain_compatible
---
license: mit
tags:
- fill-mask
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-large-dapt-scientific-papers-pubmed-tapt
  results: []
---

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# deberta-v3-large-dapt-scientific-papers-pubmed-tapt

This model is a fine-tuned version of [domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed](https://huggingface.co/domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4429
- Accuracy: 0.5915

## 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-05
- 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 3.3855        | 1.0   | 4134  | 3.2334          | 0.4953   |
| 2.9224        | 2.0   | 8268  | 2.8317          | 0.5430   |
| 2.703         | 3.0   | 12402 | 2.6141          | 0.5665   |
| 2.4963        | 4.0   | 16536 | 2.4918          | 0.5855   |
| 2.399         | 5.0   | 20670 | 2.4429          | 0.5915   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
