transformers tensorboard safetensors whisper audio-classification generated_from_trainer base_model:openai/whisper-small license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: whisper-small-lang-id
  results: []
---

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# whisper-small-lang-id

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3220
- Accuracy: 0.9555
- F1: 0.9549

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.0498        | 0.25  | 2500  | 0.2722          | 0.9578   | 0.9576 |
| 0.0039        | 1.12  | 5000  | 0.6877          | 0.8952   | 0.8901 |
| 0.0           | 1.38  | 7500  | 0.2562          | 0.9532   | 0.9526 |
| 0.0           | 2.25  | 10000 | 0.3220          | 0.9555   | 0.9549 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
