---
base_model: facebook/wav2vec2-base-960h
library_name: transformers
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-base-960h-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. -->

# wav2vec2-base-960h-EMOPIA

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4624
- Accuracy: 0.6620

## 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-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2041        | 1.0   | 807   | 1.1999          | 0.3662   |
| 1.067         | 2.0   | 1614  | 1.4613          | 0.4507   |
| 1.1007        | 3.0   | 2421  | 1.5213          | 0.4085   |
| 1.1945        | 4.0   | 3228  | 1.6642          | 0.6056   |
| 1.3665        | 5.0   | 4035  | 2.9908          | 0.4366   |
| 1.4506        | 6.0   | 4842  | 1.9230          | 0.6056   |
| 1.495         | 7.0   | 5649  | 1.6813          | 0.6761   |
| 1.2605        | 8.0   | 6456  | 1.8937          | 0.6620   |
| 1.2713        | 9.0   | 7263  | 1.6284          | 0.6901   |
| 1.2608        | 10.0  | 8070  | 1.9438          | 0.6479   |
| 1.2068        | 11.0  | 8877  | 1.5237          | 0.7183   |
| 1.0478        | 12.0  | 9684  | 2.0007          | 0.6338   |
| 1.1282        | 13.0  | 10491 | 1.5307          | 0.7465   |
| 0.9433        | 14.0  | 11298 | 2.0042          | 0.6479   |
| 0.9574        | 15.0  | 12105 | 2.1985          | 0.6338   |
| 0.8737        | 16.0  | 12912 | 2.1568          | 0.6479   |
| 0.8937        | 17.0  | 13719 | 2.2980          | 0.6197   |
| 0.8681        | 18.0  | 14526 | 2.3268          | 0.6197   |
| 0.8005        | 19.0  | 15333 | 2.4827          | 0.6479   |
| 0.8176        | 20.0  | 16140 | 2.4842          | 0.6338   |
| 0.8133        | 21.0  | 16947 | 2.0620          | 0.6761   |
| 0.7404        | 22.0  | 17754 | 2.4148          | 0.6479   |
| 0.7134        | 23.0  | 18561 | 2.3389          | 0.6761   |
| 0.6573        | 24.0  | 19368 | 2.6972          | 0.6197   |
| 0.6848        | 25.0  | 20175 | 2.3375          | 0.6761   |
| 0.6161        | 26.0  | 20982 | 2.4791          | 0.6620   |
| 0.6301        | 27.0  | 21789 | 2.3807          | 0.6479   |
| 0.5758        | 28.0  | 22596 | 2.2243          | 0.6901   |
| 0.5598        | 29.0  | 23403 | 2.4130          | 0.6620   |
| 0.6066        | 30.0  | 24210 | 2.4624          | 0.6620   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1