---
license: apache-2.0
base_model: jonatasgrosman/wav2vec2-large-xlsr-53-english
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-large-xlsr-53-english-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-large-xlsr-53-english-finetuned-ravdess-v8

This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6533
- Accuracy: 0.7222

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1363        | 0.15  | 25   | 1.0081          | 0.7778   |
| 0.1327        | 0.31  | 50   | 0.9010          | 0.8125   |
| 0.1415        | 0.46  | 75   | 1.4153          | 0.7153   |
| 0.185         | 0.62  | 100  | 1.7617          | 0.7083   |
| 0.2158        | 0.77  | 125  | 2.1611          | 0.6597   |
| 0.4308        | 0.93  | 150  | 2.0827          | 0.6597   |
| 0.3191        | 1.08  | 175  | 2.2436          | 0.6319   |
| 0.3377        | 1.23  | 200  | 1.7225          | 0.6944   |
| 0.232         | 1.39  | 225  | 1.5759          | 0.7292   |
| 0.2571        | 1.54  | 250  | 1.8838          | 0.7222   |
| 0.2376        | 1.7   | 275  | 1.5548          | 0.7222   |
| 0.1417        | 1.85  | 300  | 1.2785          | 0.75     |
| 0.0731        | 2.01  | 325  | 1.4898          | 0.7431   |
| 0.0852        | 2.16  | 350  | 1.3757          | 0.75     |
| 0.0517        | 2.31  | 375  | 1.4918          | 0.7361   |
| 0.1537        | 2.47  | 400  | 1.4951          | 0.7431   |
| 0.0309        | 2.62  | 425  | 1.5893          | 0.7292   |
| 0.0021        | 2.78  | 450  | 1.6348          | 0.7292   |
| 0.0394        | 2.93  | 475  | 1.6533          | 0.7222   |


### Framework versions

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