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---
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
|