metadata
tags:
- generated_from_trainer
datasets:
- big_patent
model-index:
- name: reformer-finetuned-big_patent
results: []
reformer-finetuned-big_patent
This model is a fine-tuned version of robingeibel/reformer-finetuned-big_patent on the big_patent dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
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: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|
| 0.0 | 1.0 | 15011 | 0.0000 |
| 0.0 | 2.0 | 30022 | 0.0000 |
| 0.0 | 3.0 | 45033 | 0.0000 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1