---
library_name: transformers
license: apache-2.0
base_model: r-f/wav2vec-english-speech-emotion-recognition
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [r-f/wav2vec-english-speech-emotion-recognition](https://huggingface.co/r-f/wav2vec-english-speech-emotion-recognition) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1011
- Accuracy: 0.9724

## 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: 0.001
- train_batch_size: 10
- eval_batch_size: 5
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4918        | 1.0   | 232  | 1.3591          | 0.3672   |
| 1.0899        | 2.0   | 464  | 0.9012          | 0.5672   |
| 0.9523        | 3.0   | 696  | 1.2430          | 0.4862   |
| 0.8062        | 4.0   | 928  | 0.6423          | 0.7759   |
| 0.5591        | 5.0   | 1160 | 0.5161          | 0.8276   |
| 0.4538        | 6.0   | 1392 | 0.6369          | 0.8069   |
| 0.3527        | 7.0   | 1624 | 0.2526          | 0.9207   |
| 0.3833        | 8.0   | 1856 | 0.2226          | 0.9328   |
| 0.2532        | 9.0   | 2088 | 0.1955          | 0.9466   |
| 0.1296        | 10.0  | 2320 | 0.1860          | 0.9483   |
| 0.144         | 11.0  | 2552 | 0.1885          | 0.9552   |
| 0.1976        | 12.0  | 2784 | 0.1243          | 0.9655   |
| 0.0147        | 13.0  | 3016 | 0.1375          | 0.9655   |
| 0.0149        | 14.0  | 3248 | 0.1061          | 0.9776   |
| 0.0199        | 15.0  | 3480 | 0.1011          | 0.9724   |


### Framework versions

- Transformers 4.53.0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2