---
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-4c
  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-4c

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: 0.4840
- Accuracy: 0.8270

## 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: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.3113        | 0.9963  | 67   | 1.3085          | 0.3879   |
| 0.9422        | 1.9926  | 134  | 0.9515          | 0.5786   |
| 0.8097        | 2.9888  | 201  | 0.7753          | 0.6958   |
| 0.7           | 4.0     | 269  | 0.6606          | 0.7591   |
| 0.6038        | 4.9963  | 336  | 0.5957          | 0.7833   |
| 0.5796        | 5.9926  | 403  | 0.6206          | 0.7805   |
| 0.5413        | 6.9888  | 470  | 0.5471          | 0.7991   |
| 0.4974        | 8.0     | 538  | 0.5784          | 0.8009   |
| 0.4623        | 8.9963  | 605  | 0.5212          | 0.8130   |
| 0.4503        | 9.9926  | 672  | 0.5237          | 0.8242   |
| 0.428         | 10.9888 | 739  | 0.4823          | 0.8233   |
| 0.3958        | 12.0    | 807  | 0.5192          | 0.8270   |
| 0.3953        | 12.9963 | 874  | 0.4854          | 0.8270   |
| 0.3696        | 13.9926 | 941  | 0.4877          | 0.8251   |
| 0.3715        | 14.9888 | 1008 | 0.4845          | 0.8279   |
| 0.386         | 16.0    | 1076 | 0.4829          | 0.8233   |
| 0.3505        | 16.9963 | 1143 | 0.4850          | 0.8214   |
| 0.3166        | 17.9926 | 1210 | 0.4973          | 0.8270   |
| 0.366         | 18.9888 | 1277 | 0.4829          | 0.8270   |
| 0.3386        | 19.9257 | 1340 | 0.4840          | 0.8270   |


### Framework versions

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