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---
language:
- th
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- Porameht/processed-smarthome-th
metrics:
- wer
model-index:
- name: whisper-tiny-smarthome-th
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: processed-smarthome-th
type: Porameht/processed-smarthome-th
args: 'config: th, split: test'
metrics:
- name: Wer
type: wer
value: 24.375
---
<!-- 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-tiny-smarthome-th
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the processed-smarthome-th dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0546
- Wer: 24.375
## 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: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.0072 | 4.1667 | 500 | 0.0546 | 24.375 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|