---
language:
- zh
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_9_0
model-index:
- name: Whisper small zh - foriegn
  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 small zh - foriegn

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 9 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2235

## 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: 0.001
- train_batch_size: 2
- eval_batch_size: 8
- 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_steps: 50
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2446        | 0.36  | 500  | 0.3424          |
| 0.3316        | 0.73  | 1000 | 0.3260          |
| 0.2777        | 1.09  | 1500 | 0.2939          |
| 0.1808        | 1.45  | 2000 | 0.2944          |
| 0.1822        | 1.82  | 2500 | 0.2589          |
| 0.1206        | 2.18  | 3000 | 0.2468          |
| 0.0715        | 2.54  | 3500 | 0.2319          |
| 0.0642        | 2.91  | 4000 | 0.2235          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0