pytorch tensorboard deberta fill-mask transformers generated_from_trainer license:mit model-index autotrain_compatible
---
license: mit
tags:
- generated_from_trainer
model-index:
- name: nbme-deberta-large
  results: []
---

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# nbme-deberta-large

This model is a fine-tuned version of [microsoft/deberta-large](https://huggingface.co/microsoft/deberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8806

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.358         | 1.0   | 1850 | 1.1622          |
| 1.0073        | 2.0   | 3700 | 0.9461          |
| 0.8837        | 3.0   | 5550 | 0.8806          |


### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
