---
license: apache-2.0
base_model: facebook/wav2vec2-large-robust-ft-libri-960h
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-large-robust-ft-libri-960h-finetuned-ravdess-v3
  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-robust-ft-libri-960h-finetuned-ravdess-v3

This model is a fine-tuned version of [facebook/wav2vec2-large-robust-ft-libri-960h](https://huggingface.co/facebook/wav2vec2-large-robust-ft-libri-960h) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9736
- Accuracy: 0.6354

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0795        | 1.0   | 18   | 2.0783          | 0.1007   |
| 2.0703        | 2.0   | 36   | 2.0743          | 0.1181   |
| 2.062         | 3.0   | 54   | 2.0632          | 0.1597   |
| 2.0444        | 4.0   | 72   | 2.0439          | 0.1910   |
| 2.0031        | 5.0   | 90   | 1.9762          | 0.2778   |
| 1.9632        | 6.0   | 108  | 1.8421          | 0.3576   |
| 1.8249        | 7.0   | 126  | 1.7072          | 0.3889   |
| 1.6733        | 8.0   | 144  | 1.5729          | 0.3819   |
| 1.5452        | 9.0   | 162  | 1.4826          | 0.4201   |
| 1.4479        | 10.0  | 180  | 1.4214          | 0.4236   |
| 1.443         | 11.0  | 198  | 1.3441          | 0.4340   |
| 1.3341        | 12.0  | 216  | 1.3241          | 0.5      |
| 1.2697        | 13.0  | 234  | 1.2810          | 0.5069   |
| 1.2348        | 14.0  | 252  | 1.2349          | 0.5069   |
| 1.1785        | 15.0  | 270  | 1.1948          | 0.5208   |
| 1.1687        | 16.0  | 288  | 1.1831          | 0.5451   |
| 1.1168        | 17.0  | 306  | 1.1481          | 0.5764   |
| 1.0975        | 18.0  | 324  | 1.1342          | 0.5764   |
| 1.0491        | 19.0  | 342  | 1.1138          | 0.6146   |
| 1.033         | 20.0  | 360  | 1.0800          | 0.6146   |
| 1.0523        | 21.0  | 378  | 1.0678          | 0.6146   |
| 1.0136        | 22.0  | 396  | 1.0472          | 0.6111   |
| 0.9777        | 23.0  | 414  | 1.0175          | 0.6111   |
| 1.0007        | 24.0  | 432  | 1.0703          | 0.6215   |
| 0.9584        | 25.0  | 450  | 0.9935          | 0.6181   |
| 0.9102        | 26.0  | 468  | 0.9736          | 0.6354   |
| 0.9101        | 27.0  | 486  | 0.9758          | 0.6285   |
| 0.9405        | 28.0  | 504  | 0.9659          | 0.6319   |
| 0.9366        | 29.0  | 522  | 0.9719          | 0.625    |
| 0.9498        | 30.0  | 540  | 0.9713          | 0.6215   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3