---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-xlsr-korean-speech-emotion-recognition3
  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-xlsr-korean-speech-emotion-recognition3

This model is a fine-tuned version of [jungjongho/wav2vec2-large-xlsr-korean-demo-colab_epoch15](https://huggingface.co/jungjongho/wav2vec2-large-xlsr-korean-demo-colab_epoch15) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0600
- Accuracy: 0.9876

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6472        | 0.08  | 1500  | 0.3769          | 0.8705   |
| 0.3873        | 0.15  | 3000  | 0.3814          | 0.9127   |
| 0.3002        | 0.23  | 4500  | 0.2617          | 0.9429   |
| 0.2399        | 0.3   | 6000  | 0.1336          | 0.9693   |
| 0.2181        | 0.38  | 7500  | 0.1360          | 0.9728   |
| 0.1992        | 0.46  | 9000  | 0.1239          | 0.9717   |
| 0.1556        | 0.53  | 10500 | 0.1053          | 0.9781   |
| 0.1412        | 0.61  | 12000 | 0.0915          | 0.9810   |
| 0.1396        | 0.69  | 13500 | 0.0777          | 0.9826   |
| 0.1159        | 0.76  | 15000 | 0.0801          | 0.9831   |
| 0.1156        | 0.84  | 16500 | 0.0667          | 0.9867   |
| 0.1149        | 0.91  | 18000 | 0.0670          | 0.9860   |
| 0.0929        | 0.99  | 19500 | 0.0600          | 0.9876   |


### Framework versions

- Transformers 4.22.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.4.1.dev0
- Tokenizers 0.12.1