---
library_name: transformers
base_model: sandernotenbaert/okai-musiclang-content-t5-small
tags:
- generated_from_trainer
model-index:
- name: okai-musiclang-content-t5-small
  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. -->

# okai-musiclang-content-t5-small

This model is a fine-tuned version of [sandernotenbaert/okai-musiclang-content-t5-small](https://huggingface.co/sandernotenbaert/okai-musiclang-content-t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1968

## 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: 8e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4556        | 0.2226 | 500  | 1.3230          |
| 1.4166        | 0.4452 | 1000 | 1.3003          |
| 1.3956        | 0.6679 | 1500 | 1.2741          |
| 1.3865        | 0.8905 | 2000 | 1.2605          |
| 1.3589        | 1.1131 | 2500 | 1.2368          |
| 1.3514        | 1.3357 | 3000 | 1.2370          |
| 1.3349        | 1.5583 | 3500 | 1.2322          |
| 1.3163        | 1.7809 | 4000 | 1.2099          |
| 1.3183        | 2.0036 | 4500 | 1.2062          |
| 1.3204        | 2.2262 | 5000 | 1.2014          |
| 1.303         | 2.4488 | 5500 | 1.2008          |
| 1.3205        | 2.6714 | 6000 | 1.1953          |
| 1.3108        | 2.8940 | 6500 | 1.1968          |


### Framework versions

- Transformers 4.54.1
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2