---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Arousal-wav2vec2-base-EMOPIA
  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. -->

# Arousal-wav2vec2-base-EMOPIA

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4207
- Accuracy: 0.9014

## 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: 1e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 3
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6871        | 1.0   | 269  | 0.6601          | 0.6761   |
| 0.6071        | 2.0   | 538  | 0.5375          | 0.8451   |
| 0.4312        | 3.0   | 807  | 0.3544          | 0.8873   |
| 0.306         | 4.0   | 1076 | 0.3780          | 0.8592   |
| 0.3052        | 5.0   | 1345 | 0.4133          | 0.8873   |
| 0.3099        | 6.0   | 1614 | 0.4112          | 0.8873   |
| 0.2965        | 7.0   | 1883 | 0.4241          | 0.8873   |
| 0.2954        | 8.0   | 2152 | 0.4381          | 0.8873   |
| 0.2905        | 9.0   | 2421 | 0.4294          | 0.9014   |
| 0.2868        | 10.0  | 2690 | 0.4208          | 0.9014   |
| 0.284         | 11.0  | 2959 | 0.4077          | 0.9014   |
| 0.2666        | 12.0  | 3228 | 0.4149          | 0.9014   |
| 0.2697        | 13.0  | 3497 | 0.4108          | 0.9014   |
| 0.2622        | 14.0  | 3766 | 0.4187          | 0.9014   |
| 0.2648        | 15.0  | 4035 | 0.4207          | 0.9014   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1