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

# Valence-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: 1.1044
- Accuracy: 0.6761

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6979        | 1.0   | 269  | 0.6842          | 0.5915   |
| 0.69          | 2.0   | 538  | 0.6864          | 0.5775   |
| 0.6714        | 3.0   | 807  | 0.6900          | 0.5070   |
| 0.6357        | 4.0   | 1076 | 0.6514          | 0.5775   |
| 0.5678        | 5.0   | 1345 | 0.6612          | 0.6197   |
| 0.5152        | 6.0   | 1614 | 0.6496          | 0.6761   |
| 0.4826        | 7.0   | 1883 | 0.7743          | 0.6479   |
| 0.4707        | 8.0   | 2152 | 0.8348          | 0.6620   |
| 0.4742        | 9.0   | 2421 | 0.8808          | 0.6761   |
| 0.4857        | 10.0  | 2690 | 0.8734          | 0.7324   |
| 0.4779        | 11.0  | 2959 | 1.0206          | 0.6620   |
| 0.5063        | 12.0  | 3228 | 1.0737          | 0.6761   |
| 0.4776        | 13.0  | 3497 | 1.0966          | 0.6761   |
| 0.4716        | 14.0  | 3766 | 1.1046          | 0.6761   |
| 0.4672        | 15.0  | 4035 | 1.1044          | 0.6761   |


### Framework versions

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