transformers safetensors gpt2 text-generation generated_from_trainer base_model:gpt2 license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: gpt2-jp-119M
  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. -->

# gpt2-jp-119M

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3790

## 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: 156
- eval_batch_size: 156
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 7.0426        | 0.06  | 100  | 5.3865          |
| 5.0116        | 0.12  | 200  | 4.7179          |
| 4.5288        | 0.18  | 300  | 4.3459          |
| 4.2531        | 0.24  | 400  | 4.1600          |
| 4.0964        | 0.29  | 500  | 4.0072          |
| 3.9623        | 0.35  | 600  | 3.9098          |
| 3.8511        | 0.41  | 700  | 3.8118          |
| 3.7549        | 0.47  | 800  | 3.7255          |
| 3.6865        | 0.53  | 900  | 3.6480          |
| 3.6162        | 0.59  | 1000 | 3.5820          |
| 3.5471        | 0.65  | 1100 | 3.5222          |
| 3.4931        | 0.71  | 1200 | 3.4755          |
| 3.4329        | 0.77  | 1300 | 3.4319          |
| 3.4154        | 0.82  | 1400 | 3.4062          |
| 3.3766        | 0.88  | 1500 | 3.3868          |
| 3.3636        | 0.94  | 1600 | 3.3790          |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
