---
license: apache-2.0
base_model: ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-lg-xlsr-en-speech-emotion-recognition-finetuned-ravdess-v8
  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-lg-xlsr-en-speech-emotion-recognition-finetuned-ravdess-v8

This model is a fine-tuned version of [ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition](https://huggingface.co/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6778
- Accuracy: 0.75

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0178        | 0.15  | 25   | 1.8431          | 0.6181   |
| 1.7082        | 0.31  | 50   | 1.5052          | 0.5833   |
| 1.4444        | 0.46  | 75   | 1.3458          | 0.5972   |
| 1.3888        | 0.62  | 100  | 1.2760          | 0.5972   |
| 1.1819        | 0.77  | 125  | 1.1075          | 0.6667   |
| 1.1615        | 0.93  | 150  | 1.0666          | 0.625    |
| 1.1659        | 1.08  | 175  | 1.3450          | 0.5694   |
| 0.9798        | 1.23  | 200  | 0.9866          | 0.6528   |
| 0.9893        | 1.39  | 225  | 0.9311          | 0.6806   |
| 0.9357        | 1.54  | 250  | 0.9783          | 0.6736   |
| 0.7998        | 1.7   | 275  | 0.7924          | 0.7014   |
| 0.7444        | 1.85  | 300  | 0.8980          | 0.6806   |
| 0.7648        | 2.01  | 325  | 0.8994          | 0.7153   |
| 0.607         | 2.16  | 350  | 0.9416          | 0.6597   |
| 0.5551        | 2.31  | 375  | 0.7791          | 0.7431   |
| 0.5495        | 2.47  | 400  | 0.7665          | 0.7431   |
| 0.5498        | 2.62  | 425  | 0.8017          | 0.7222   |
| 0.4887        | 2.78  | 450  | 0.6967          | 0.7639   |
| 0.5308        | 2.93  | 475  | 0.6857          | 0.7569   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3