---
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: 1.0286
- Accuracy: 0.6200

## 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
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2694        | 0.98  | 41   | 1.1830          | 0.4800   |
| 1.0457        | 1.98  | 82   | 1.0959          | 0.4400   |
| 0.9201        | 2.98  | 123  | 0.9280          | 0.5600   |
| 0.8003        | 3.98  | 164  | 0.9346          | 0.7000   |
| 0.7616        | 4.98  | 205  | 0.9257          | 0.6600   |
| 0.6955        | 5.98  | 246  | 0.8411          | 0.7200   |
| 0.6743        | 6.98  | 287  | 0.9604          | 0.6200   |
| 0.5737        | 7.98  | 328  | 0.8471          | 0.7000   |
| 0.5269        | 8.98  | 369  | 1.0581          | 0.6000   |
| 0.4671        | 9.98  | 410  | 1.0365          | 0.6400   |
| 0.4227        | 10.98 | 451  | 1.0994          | 0.6000   |
| 0.3688        | 11.98 | 492  | 1.0964          | 0.5800   |
| 0.355         | 12.98 | 533  | 1.0586          | 0.5800   |
| 0.3232        | 13.98 | 574  | 1.0414          | 0.6000   |
| 0.3045        | 14.98 | 615  | 1.0286          | 0.6200   |


### Framework versions

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