---
library_name: transformers
license: mit
base_model: openai-gpt
tags:
- generated_from_trainer
model-index:
- name: gpt_1_sequence_classification_finetune
  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. -->

# gpt_1_sequence_classification_finetune

This model is a fine-tuned version of [openai-gpt](https://huggingface.co/openai-gpt) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3295

## 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: 5.38312346311055e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.6661        | 1.0   | 12   | 1.4575          |
| 1.3696        | 2.0   | 24   | 1.0023          |
| 0.6977        | 3.0   | 36   | 0.5564          |
| 0.3751        | 4.0   | 48   | 0.4573          |
| 0.2528        | 5.0   | 60   | 0.3803          |
| 0.1503        | 6.0   | 72   | 0.2699          |
| 0.0863        | 7.0   | 84   | 0.2888          |
| 0.0547        | 8.0   | 96   | 0.3295          |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0
- Datasets 3.4.0
- Tokenizers 0.21.1