---
library_name: transformers
license: cc-by-sa-4.0
base_model: airesearch/wav2vec2-large-xlsr-53-th
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-large-xlsr-53-th-speech-emotion-recognition-3c
  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-th-speech-emotion-recognition-3c

This model is a fine-tuned version of [airesearch/wav2vec2-large-xlsr-53-th](https://huggingface.co/airesearch/wav2vec2-large-xlsr-53-th) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4445
- Accuracy: 0.8492

## Model description

three emotion [Anger , Happiness , Neutral]

## 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: 3e-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: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.0305        | 0.9956  | 57   | 1.0278          | 0.4874   |
| 0.6947        | 1.9913  | 114  | 0.6649          | 0.6645   |
| 0.622         | 2.9869  | 171  | 0.5644          | 0.7607   |
| 0.5051        | 4.0     | 229  | 0.4936          | 0.7967   |
| 0.4791        | 4.9956  | 286  | 0.4235          | 0.8328   |
| 0.3918        | 5.9913  | 343  | 0.4273          | 0.8328   |
| 0.3399        | 6.9869  | 400  | 0.4316          | 0.8437   |
| 0.3473        | 8.0     | 458  | 0.4013          | 0.8448   |
| 0.3276        | 8.9956  | 515  | 0.4140          | 0.8437   |
| 0.3355        | 9.9913  | 572  | 0.4069          | 0.8459   |
| 0.2958        | 10.9869 | 629  | 0.4440          | 0.8372   |
| 0.2803        | 12.0    | 687  | 0.4381          | 0.8404   |
| 0.2996        | 12.9956 | 744  | 0.4100          | 0.8492   |
| 0.2995        | 13.9913 | 801  | 0.4310          | 0.8459   |
| 0.2645        | 14.9869 | 858  | 0.4590          | 0.8393   |
| 0.279         | 16.0    | 916  | 0.4317          | 0.8492   |
| 0.249         | 16.9956 | 973  | 0.4564          | 0.8437   |
| 0.238         | 17.9913 | 1030 | 0.4473          | 0.8459   |
| 0.209         | 18.9869 | 1087 | 0.4428          | 0.8492   |
| 0.2323        | 19.9127 | 1140 | 0.4445          | 0.8492   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1