---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
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 the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9346
- Accuracy: 0.7000

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3867        | 0.99  | 58   | 1.3518          | 0.3286   |
| 1.2842        | 1.99  | 116  | 1.1872          | 0.4571   |
| 1.0725        | 2.99  | 174  | 1.0476          | 0.5571   |
| 0.9343        | 3.99  | 232  | 0.9677          | 0.5714   |
| 0.8053        | 4.99  | 290  | 0.9525          | 0.6143   |
| 0.7895        | 5.99  | 348  | 0.7735          | 0.6857   |
| 0.6867        | 6.99  | 406  | 0.8556          | 0.6429   |
| 0.6218        | 7.99  | 464  | 0.8454          | 0.6714   |
| 0.558         | 8.99  | 522  | 0.8405          | 0.6571   |
| 0.5033        | 9.99  | 580  | 1.0190          | 0.6286   |
| 0.4403        | 10.99 | 638  | 0.8249          | 0.7000   |
| 0.3995        | 11.99 | 696  | 0.8997          | 0.7143   |
| 0.3534        | 12.99 | 754  | 0.9177          | 0.7000   |
| 0.3023        | 13.99 | 812  | 0.9544          | 0.6571   |
| 0.2752        | 14.99 | 870  | 0.9346          | 0.7000   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1