---
library_name: transformers
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: gpt2-poems-finetuned-v1
  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-poems-finetuned-v1

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: 3.8988

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.2281        | 0.3193 | 500  | 4.0769          |
| 4.1077        | 0.6385 | 1000 | 4.0222          |
| 4.0667        | 0.9578 | 1500 | 3.9898          |
| 4.0905        | 1.2765 | 2000 | 3.9738          |
| 4.008         | 1.5957 | 2500 | 3.9561          |
| 4.0071        | 1.9150 | 3000 | 3.9448          |
| 3.9696        | 2.2337 | 3500 | 3.9376          |
| 3.9984        | 2.5530 | 4000 | 3.9289          |
| 3.9279        | 2.8722 | 4500 | 3.9212          |
| 3.9569        | 3.1909 | 5000 | 3.9181          |
| 3.9598        | 3.5102 | 5500 | 3.9154          |
| 3.9403        | 3.8294 | 6000 | 3.9126          |
| 3.908         | 4.1481 | 6500 | 3.9117          |
| 3.9344        | 4.4674 | 7000 | 3.9109          |
| 3.9645        | 4.7867 | 7500 | 3.9105          |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.9.1+cu126
- Datasets 4.5.0
- Tokenizers 0.22.2