---
library_name: transformers
license: mit
base_model: openai-community/gpt2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clm-gpt2
  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. -->

# clm-gpt2

This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5054
- Accuracy: 0.6325

## 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: 0.003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 2.4536        | 0.1302 | 500   | 2.1316          | 0.4955   |
| 2.1054        | 0.2603 | 1000  | 2.0124          | 0.5221   |
| 1.9756        | 0.3905 | 1500  | 1.9025          | 0.5453   |
| 1.8863        | 0.5206 | 2000  | 1.8367          | 0.5601   |
| 1.8283        | 0.6508 | 2500  | 1.7927          | 0.5686   |
| 1.7893        | 0.7809 | 3000  | 1.7585          | 0.5760   |
| 1.7555        | 0.9111 | 3500  | 1.7328          | 0.5815   |
| 1.7143        | 1.0413 | 4000  | 1.7016          | 0.5882   |
| 1.6697        | 1.1714 | 4500  | 1.6813          | 0.5930   |
| 1.6584        | 1.3016 | 5000  | 1.6615          | 0.5972   |
| 1.6438        | 1.4317 | 5500  | 1.6422          | 0.6009   |
| 1.6184        | 1.5619 | 6000  | 1.6236          | 0.6049   |
| 1.6086        | 1.6920 | 6500  | 1.6102          | 0.6082   |
| 1.5882        | 1.8222 | 7000  | 1.5938          | 0.6114   |
| 1.5719        | 1.9524 | 7500  | 1.5786          | 0.6148   |
| 1.5272        | 2.0825 | 8000  | 1.5718          | 0.6175   |
| 1.4971        | 2.2127 | 8500  | 1.5593          | 0.6204   |
| 1.4893        | 2.3428 | 9000  | 1.5475          | 0.6227   |
| 1.4808        | 2.4730 | 9500  | 1.5382          | 0.6251   |
| 1.4689        | 2.6031 | 10000 | 1.5274          | 0.6275   |
| 1.4572        | 2.7333 | 10500 | 1.5169          | 0.6298   |
| 1.4488        | 2.8635 | 11000 | 1.5106          | 0.6315   |
| 1.4465        | 2.9936 | 11500 | 1.5054          | 0.6325   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1