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---
library_name: transformers
language:
- th
license: apache-2.0
base_model: openai/whisper-medium
tags:
- asr
- speech-recognition
- thai
- custom-model
- fine-tuning
- Common Voice
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Medium TH - Common Voice 17
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_17_0
type: common_voice_17_0
config: th
split: validation[:20%]
args: th
metrics:
- name: Wer
type: wer
value: 81.60690571049138
---
<!-- 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 Medium TH - Common Voice 17
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2987
- Wer: 81.6069
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 125
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.5323 | 0.6083 | 250 | 0.4352 | 91.2683 |
| 0.2568 | 1.2165 | 500 | 0.3432 | 87.1514 |
| 0.2126 | 1.8248 | 750 | 0.3047 | 83.3333 |
| 0.0974 | 2.4331 | 1000 | 0.2987 | 81.6069 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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