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---
license: mit
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: all-base-rerun-new-loop
  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. -->

# all-base-rerun-new-loop

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0966

## 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: 0.0005
- 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: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.3514        | 0.29  | 500   | 5.3344          |
| 5.0244        | 0.58  | 1000  | 4.9301          |
| 4.6948        | 0.87  | 1500  | 4.6847          |
| 4.4421        | 1.16  | 2000  | 4.5356          |
| 4.285         | 1.46  | 2500  | 4.4193          |
| 4.1724        | 1.75  | 3000  | 4.3179          |
| 4.0767        | 2.04  | 3500  | 4.2422          |
| 3.883         | 2.33  | 4000  | 4.1998          |
| 3.8483        | 2.62  | 4500  | 4.1495          |
| 3.8125        | 2.91  | 5000  | 4.0986          |
| 3.6378        | 3.2   | 5500  | 4.0910          |
| 3.5732        | 3.49  | 6000  | 4.0640          |
| 3.5575        | 3.78  | 6500  | 4.0288          |
| 3.4696        | 4.07  | 7000  | 4.0250          |
| 3.3036        | 4.37  | 7500  | 4.0232          |
| 3.2977        | 4.66  | 8000  | 4.0094          |
| 3.2899        | 4.95  | 8500  | 3.9977          |
| 3.1442        | 5.24  | 9000  | 4.0094          |
| 3.1227        | 5.53  | 9500  | 4.0079          |
| 3.1169        | 5.82  | 10000 | 4.0071          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3