---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-large-robust-12-ft-emotion-msp-dim-finetuned-gtzan
  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. -->

# wav2vec2-large-robust-12-ft-emotion-msp-dim-finetuned-gtzan

This model is a fine-tuned version of [audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim](https://huggingface.co/audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7711
- Accuracy: 0.83

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.186         | 1.0   | 112  | 2.1638          | 0.3      |
| 1.655         | 2.0   | 225  | 1.7677          | 0.48     |
| 1.5148        | 3.0   | 337  | 1.3746          | 0.54     |
| 1.2349        | 4.0   | 450  | 1.1218          | 0.64     |
| 0.9702        | 5.0   | 562  | 1.0244          | 0.69     |
| 0.9191        | 6.0   | 675  | 0.9180          | 0.75     |
| 0.6891        | 7.0   | 787  | 0.8959          | 0.76     |
| 0.628         | 8.0   | 900  | 0.8084          | 0.81     |
| 0.7337        | 9.0   | 1012 | 0.7742          | 0.83     |
| 0.5573        | 9.96  | 1120 | 0.7711          | 0.83     |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3