whisper-small-th / README.md
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---
language:
- th
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Thai
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 th
type: mozilla-foundation/common_voice_11_0
config: th
split: test
args: th
metrics:
- type: wer
value: 14.060702592690913
name: Wer
- type: mer
value: 13.786820528393562
name: Mer
---
<!-- 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 Thai
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 th,None,th_th dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1841
- Wer: 14.060
## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0909 | 0.2 | 1000 | 0.3373 | 25.5752 |
| 0.0426 | 1.1 | 2000 | 0.2540 | 20.9739 |
| 0.0267 | 2.0 | 3000 | 0.2210 | 17.4080 |
| 0.0145 | 2.2 | 4000 | 0.2134 | 15.5675 |
| 0.0099 | 3.1 | 5000 | 0.1841 | 13.2285 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2