---
license: mit
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: all-base
  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

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: 4.0367

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.355         | 0.29  | 500   | 5.3170          |
| 5.0354        | 0.58  | 1000  | 4.8924          |
| 4.6989        | 0.87  | 1500  | 4.6507          |
| 4.4441        | 1.16  | 2000  | 4.5047          |
| 4.2822        | 1.45  | 2500  | 4.3873          |
| 4.1851        | 1.74  | 3000  | 4.2815          |
| 4.0807        | 2.02  | 3500  | 4.2026          |
| 3.8813        | 2.31  | 4000  | 4.1635          |
| 3.8547        | 2.6   | 4500  | 4.1118          |
| 3.8136        | 2.89  | 5000  | 4.0571          |
| 3.646         | 3.18  | 5500  | 4.0499          |
| 3.5714        | 3.47  | 6000  | 4.0237          |
| 3.5592        | 3.76  | 6500  | 3.9907          |
| 3.4929        | 4.05  | 7000  | 3.9792          |
| 3.3028        | 4.34  | 7500  | 3.9795          |
| 3.2966        | 4.63  | 8000  | 3.9665          |
| 3.2851        | 4.92  | 8500  | 3.9538          |
| 3.1662        | 5.21  | 9000  | 3.9633          |
| 3.1138        | 5.49  | 9500  | 3.9624          |
| 3.1152        | 5.78  | 10000 | 3.9615          |


### Framework versions

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