---
license: apache-2.0
tags:
- audio-classification
- generated_from_trainer
datasets:
- common_language
metrics:
- accuracy
base_model: openai/whisper-base
model-index:
- name: whisper-base-ft-common-language-id
  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. -->

# whisper-base-ft-common-language-id

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the common_language dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0725
- Accuracy: 0.7525

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.5291        | 1.0   | 694  | 2.4787          | 0.4806   |
| 1.5801        | 2.0   | 1388 | 1.6258          | 0.6260   |
| 1.0144        | 3.0   | 2082 | 1.2886          | 0.6816   |
| 0.7442        | 4.0   | 2776 | 1.0783          | 0.7237   |
| 0.4802        | 5.0   | 3470 | 1.0582          | 0.7266   |
| 0.3378        | 6.0   | 4164 | 1.0173          | 0.7417   |
| 0.1941        | 7.0   | 4858 | 1.0054          | 0.7446   |
| 0.1424        | 8.0   | 5552 | 1.0213          | 0.7508   |
| 0.1242        | 9.0   | 6246 | 1.0567          | 0.7495   |
| 0.1527        | 10.0  | 6940 | 1.0725          | 0.7525   |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.13.2