---
language:
- zh
license: apache-2.0
library_name: peft
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_15_0
base_model: openai/whisper-small
model-index:
- name: Whisper small TW - AlanDlink
  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 TW - AlanDlink

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 15.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2175

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2151        | 1.33  | 1000 | 2.1197          |
| 0.5107        | 2.67  | 2000 | 0.4872          |
| 0.294         | 4.0   | 3000 | 0.2780          |
| 0.229         | 5.33  | 4000 | 0.2428          |
| 0.2193        | 6.67  | 5000 | 0.2278          |
| 0.2292        | 8.0   | 6000 | 0.2213          |
| 0.2288        | 9.33  | 7000 | 0.2184          |
| 0.2065        | 10.67 | 8000 | 0.2175          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0