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---
language:
- th
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-small
datasets:
- aicookcook
metrics:
- wer
model-index:
- name: all_asr
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: aicookcook
type: aicookcook
args: config:th
metrics:
- type: wer
value: 18.262970669172425
name: Wer
---
<!-- 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. -->
# all_asr
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the aicookcook dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1879
- Wer: 18.2630
## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0586 | 3.0048 | 2500 | 0.1755 | 19.9779 |
| 0.0038 | 6.0096 | 5000 | 0.1879 | 18.2630 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|