---
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-v5
  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-v5

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: 0.8443
- Accuracy: 0.7257

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 9    | 2.0697          | 0.1424   |
| 2.0767        | 2.0   | 18   | 2.0585          | 0.2292   |
| 2.0642        | 3.0   | 27   | 2.0382          | 0.2118   |
| 2.0463        | 4.0   | 36   | 1.9870          | 0.2361   |
| 1.9984        | 5.0   | 45   | 1.8878          | 0.3160   |
| 1.8817        | 6.0   | 54   | 1.7381          | 0.3785   |
| 1.743         | 7.0   | 63   | 1.6483          | 0.4062   |
| 1.6047        | 8.0   | 72   | 1.5459          | 0.4340   |
| 1.4919        | 9.0   | 81   | 1.4229          | 0.4653   |
| 1.4067        | 10.0  | 90   | 1.3539          | 0.4479   |
| 1.4067        | 11.0  | 99   | 1.2584          | 0.5243   |
| 1.3039        | 12.0  | 108  | 1.2465          | 0.5243   |
| 1.2376        | 13.0  | 117  | 1.1980          | 0.5451   |
| 1.1504        | 14.0  | 126  | 1.1339          | 0.625    |
| 1.0479        | 15.0  | 135  | 1.1273          | 0.6007   |
| 0.9986        | 16.0  | 144  | 1.0976          | 0.6215   |
| 0.9289        | 17.0  | 153  | 1.0150          | 0.6528   |
| 0.9288        | 18.0  | 162  | 0.9629          | 0.6667   |
| 0.8092        | 19.0  | 171  | 0.9882          | 0.6528   |
| 0.7641        | 20.0  | 180  | 0.9357          | 0.6806   |
| 0.7641        | 21.0  | 189  | 0.9578          | 0.6840   |
| 0.7073        | 22.0  | 198  | 0.8655          | 0.6806   |
| 0.7277        | 23.0  | 207  | 1.0007          | 0.6632   |
| 0.6614        | 24.0  | 216  | 0.8399          | 0.7222   |
| 0.6571        | 25.0  | 225  | 0.8995          | 0.6875   |
| 0.6304        | 26.0  | 234  | 0.8523          | 0.7118   |
| 0.6298        | 27.0  | 243  | 0.8918          | 0.7049   |
| 0.5929        | 28.0  | 252  | 0.8510          | 0.7222   |
| 0.5915        | 29.0  | 261  | 0.8443          | 0.7257   |
| 0.5807        | 30.0  | 270  | 0.8536          | 0.7257   |


### Framework versions

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