---
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
  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

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: 0.8209
- Accuracy: 0.6849

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4531        | 1.0   | 89   | 1.3187          | 0.4384   |
| 1.1932        | 2.0   | 178  | 1.1075          | 0.5416   |
| 0.984         | 3.0   | 267  | 0.9787          | 0.6024   |
| 0.9603        | 4.0   | 356  | 0.9281          | 0.6224   |
| 0.8789        | 5.0   | 445  | 0.9141          | 0.6361   |
| 0.9113        | 6.0   | 534  | 0.8611          | 0.6568   |
| 0.8453        | 7.0   | 623  | 0.8444          | 0.6656   |
| 0.7558        | 8.0   | 712  | 0.8257          | 0.6776   |
| 0.784         | 9.0   | 801  | 0.8341          | 0.6783   |
| 0.7566        | 10.0  | 890  | 0.8209          | 0.6849   |


### Framework versions

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