metadata
library_name: transformers
language:
- th
license: apache-2.0
base_model: biodatlab/whisper-th-small-combined
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small Th Combined Finetuned
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: th
split: test
args: 'config: th, split: validated'
metrics:
- name: Wer
type: wer
value: 0.41320489664860527
Whisper Small Th Combined Finetuned
This model is a fine-tuned version of biodatlab/whisper-th-small-combined on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0702
- Wer: 0.4132
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3362 | 0.2175 | 1000 | 0.1439 | 0.6061 |
| 0.2993 | 0.4349 | 2000 | 0.1230 | 0.5645 |
| 0.2523 | 0.6524 | 3000 | 0.1080 | 0.5299 |
| 0.2823 | 0.8698 | 4000 | 0.0939 | 0.4914 |
| 0.2459 | 1.0873 | 5000 | 0.0840 | 0.4570 |
| 0.2005 | 1.3047 | 6000 | 0.0776 | 0.4364 |
| 0.2081 | 1.5222 | 7000 | 0.0724 | 0.4157 |
| 0.1918 | 1.7396 | 8000 | 0.0702 | 0.4132 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0