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---
base_model: google/reformer-crime-and-punishment
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: reformer_model
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. -->
# reformer_model
This model is a fine-tuned version of [google/reformer-crime-and-punishment](https://huggingface.co/google/reformer-crime-and-punishment) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6693
- Accuracy: 0.561
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6841 | 1.0 | 625 | 0.6725 | 0.559 |
| 0.6789 | 2.0 | 1250 | 0.6693 | 0.561 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cpu
- Datasets 2.19.1
- Tokenizers 0.19.1
|