---
license: apache-2.0
base_model: SpeechFlow/spoken_language_identification
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: AudioClassification
  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. -->

# AudioClassification

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9903
- Accuracy: 0.35 

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6783        | 0.98  | 11   | 1.0771          | 0.21     |
| 0.6614        | 1.96  | 22   | 0.9514          | 0.25     |
| 0.6628        | 2.93  | 33   | 0.9843          | 0.28     |
| 0.6629        | 4.0   | 45   | 1.0408          | 0.27     |
| 0.6583        | 4.98  | 56   | 1.0061          | 0.29     |
| 0.6623        | 5.96  | 67   | 1.0227          | 0.31     |
| 0.6613        | 6.93  | 78   | 1.0398          | 0.30     |
| 0.6635        | 8.0   | 90   | 1.0085          | 0.29     |
| 0.6577        | 8.98  | 101  | 0.9842          | 0.34     |
| 0.6629        | 9.78  | 110  | 0.9903          | 0.35     |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1