---
library_name: transformers
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: music-generation
  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. -->

# music-generation

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: 0.5312

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- 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: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 3.7238        | 0.9217  | 100  | 2.8460          |
| 2.4643        | 1.8387  | 200  | 1.8829          |
| 1.8339        | 2.7558  | 300  | 1.4234          |
| 1.5013        | 3.6728  | 400  | 1.2203          |
| 1.3125        | 4.5899  | 500  | 1.0966          |
| 1.1899        | 5.5069  | 600  | 1.0028          |
| 1.0982        | 6.4240  | 700  | 0.9353          |
| 1.0302        | 7.3410  | 800  | 0.8779          |
| 0.9766        | 8.2581  | 900  | 0.8276          |
| 0.9243        | 9.1751  | 1000 | 0.7757          |
| 0.8825        | 10.0922 | 1100 | 0.7345          |
| 0.845         | 11.0092 | 1200 | 0.7000          |
| 0.8083        | 11.9309 | 1300 | 0.6624          |
| 0.7784        | 12.8479 | 1400 | 0.6328          |
| 0.7502        | 13.7650 | 1500 | 0.6052          |
| 0.7281        | 14.6820 | 1600 | 0.5816          |
| 0.7072        | 15.5991 | 1700 | 0.5622          |
| 0.6903        | 16.5161 | 1800 | 0.5486          |
| 0.6796        | 17.4332 | 1900 | 0.5386          |
| 0.6705        | 18.3502 | 2000 | 0.5335          |
| 0.6646        | 19.2673 | 2100 | 0.5312          |


### Framework versions

- Transformers 4.55.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4