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---
base_model: openai/whisper-small
datasets:
- mozilla-foundation/common_voice_16_1
language:
- nan
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: Whisper small Taiwanese - LoRA
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 Taiwanese - LoRA
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8997
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.0204 | 1.0 | 2572 | 1.0091 |
| 0.9044 | 2.0 | 5144 | 0.9392 |
| 0.7166 | 3.0 | 7716 | 0.8862 |
| 0.5224 | 4.0 | 10288 | 0.9016 |
| 0.5268 | 5.0 | 12860 | 0.8868 |
| 0.3808 | 6.0 | 15432 | 0.8997 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |