metadata
language:
- th
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- fruk19/N_asr
metrics:
- wer
model-index:
- name: North_asri
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: aicookcook
type: fruk19/N_asr
args: 'config: th'
metrics:
- name: Wer
type: wer
value: 6.260140616549487
North_asri
This model is a fine-tuned version of openai/whisper-small on the aicookcook dataset. It achieves the following results on the evaluation set:
- Loss: 0.0739
- Wer: 6.2601
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 99
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.099 | 1.0 | 3000 | 0.1002 | 10.8545 |
0.0342 | 2.0 | 6000 | 0.0776 | 7.1390 |
0.0098 | 3.0 | 9000 | 0.0739 | 6.2601 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1