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

# 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: 2.1691
- Accuracy: 0.6338

## 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
- 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
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8716        | 1.0   | 269  | 0.9822          | 0.6197   |
| 0.8143        | 2.0   | 538  | 1.2324          | 0.5352   |
| 0.7584        | 3.0   | 807  | 1.0226          | 0.6479   |
| 0.6715        | 4.0   | 1076 | 0.9550          | 0.6620   |
| 0.6471        | 5.0   | 1345 | 1.1272          | 0.6761   |
| 0.5759        | 6.0   | 1614 | 1.2193          | 0.6761   |
| 0.4963        | 7.0   | 1883 | 1.2214          | 0.7183   |
| 0.4053        | 8.0   | 2152 | 1.3083          | 0.7465   |
| 0.3344        | 9.0   | 2421 | 1.6391          | 0.6620   |
| 0.3216        | 10.0  | 2690 | 1.7224          | 0.6479   |
| 0.2248        | 11.0  | 2959 | 1.7973          | 0.6761   |
| 0.1982        | 12.0  | 3228 | 2.0241          | 0.6479   |
| 0.1362        | 13.0  | 3497 | 1.9933          | 0.6479   |
| 0.0879        | 14.0  | 3766 | 2.0865          | 0.6479   |
| 0.0712        | 15.0  | 4035 | 2.1691          | 0.6338   |


### Framework versions

- Transformers 4.42.2
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1