---
license: apache-2.0
tags:
- Speech-Emotion-Recognition
- generated_from_trainer
datasets:
- dusha_emotion_audio
metrics:
- accuracy
model-index:
- name: Wav2vec2-xls-r-300m
  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-xls-r-300m

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the KELONMYOSA/dusha_emotion_audio dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5633
- Accuracy: 0.7970

## 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: 0.003
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.7868        | 1.0   | 24170  | 0.7561          | 0.7318   |
| 0.7147        | 2.0   | 48340  | 0.6984          | 0.7459   |
| 0.669         | 3.0   | 72510  | 0.6263          | 0.7727   |
| 0.6362        | 4.0   | 96680  | 0.5832          | 0.7902   |
| 0.4476        | 5.0   | 120850 | 0.5633          | 0.7970   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3