pytorch tensorboard reformer fill-mask dataset:big_patent transformers generated_from_trainer model-index autotrain_compatible
---
tags:
- generated_from_trainer
datasets:
- big_patent
model-index:
- name: reformer-finetuned-big_patent-16384
  results: []
---

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# reformer-finetuned-big_patent-16384

This model is a fine-tuned version of [robingeibel/reformer-finetuned-big_patent-wikipedia-arxiv-16384](https://huggingface.co/robingeibel/reformer-finetuned-big_patent-wikipedia-arxiv-16384) on the big_patent dataset.
It achieves the following results on the evaluation set:
- Loss: 6.7382

## 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: 2.5e-06
- 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: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 6.7398        | 1.0   | 53286  | 6.7243          |
| 6.7449        | 2.0   | 106572 | 6.7388          |
| 6.7534        | 3.0   | 159858 | 6.7382          |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
