---
tags:
- generated_from_trainer
model-index:
- name: model
  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. -->

# model

This model is a fine-tuned version of [floriangardin/musiclang_medium](https://huggingface.co/floriangardin/musiclang_medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5640

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 15
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| No log        | 0.15  | 400   | 0.6429          |
| 0.6819        | 0.3   | 800   | 0.6389          |
| 0.6744        | 0.44  | 1200  | 0.6335          |
| 0.6664        | 0.59  | 1600  | 0.6319          |
| 0.659         | 0.74  | 2000  | 0.6246          |
| 0.659         | 0.89  | 2400  | 0.6203          |
| 0.6519        | 1.04  | 2800  | 0.6178          |
| 0.6446        | 1.19  | 3200  | 0.6136          |
| 0.6403        | 1.33  | 3600  | 0.6103          |
| 0.6363        | 1.48  | 4000  | 0.6052          |
| 0.6363        | 1.63  | 4400  | 0.6051          |
| 0.6302        | 1.78  | 4800  | 0.6011          |
| 0.6257        | 1.93  | 5200  | 0.5985          |
| 0.6229        | 2.07  | 5600  | 0.5971          |
| 0.6185        | 2.22  | 6000  | 0.5948          |
| 0.6185        | 2.37  | 6400  | 0.5938          |
| 0.6155        | 2.52  | 6800  | 0.5911          |
| 0.6123        | 2.67  | 7200  | 0.5883          |
| 0.6096        | 2.82  | 7600  | 0.5867          |
| 0.6079        | 2.96  | 8000  | 0.5856          |
| 0.6079        | 3.11  | 8400  | 0.5835          |
| 0.6026        | 3.26  | 8800  | 0.5814          |
| 0.5998        | 3.41  | 9200  | 0.5804          |
| 0.5993        | 3.56  | 9600  | 0.5779          |
| 0.5978        | 3.71  | 10000 | 0.5770          |
| 0.5978        | 3.85  | 10400 | 0.5761          |
| 0.5958        | 4.0   | 10800 | 0.5746          |
| 0.5937        | 4.15  | 11200 | 0.5737          |
| 0.5909        | 4.3   | 11600 | 0.5733          |
| 0.5884        | 4.45  | 12000 | 0.5714          |
| 0.5884        | 4.59  | 12400 | 0.5704          |
| 0.588         | 4.74  | 12800 | 0.5690          |
| 0.5875        | 4.89  | 13200 | 0.5685          |
| 0.5848        | 5.04  | 13600 | 0.5679          |
| 0.5827        | 5.19  | 14000 | 0.5668          |
| 0.5827        | 5.34  | 14400 | 0.5663          |
| 0.5839        | 5.48  | 14800 | 0.5658          |
| 0.5806        | 5.63  | 15200 | 0.5650          |
| 0.5803        | 5.78  | 15600 | 0.5644          |
| 0.5796        | 5.93  | 16000 | 0.5640          |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3