metadata
language:
- ta
license: apache-2.0
base_model: openai/whisper-base
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Breeze DSW Tamil - base
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_16_0 ta
type: mozilla-foundation/common_voice_16_0
config: ta
split: test
args: ta
metrics:
- name: Wer
type: wer
value: 21.407068619939793
Breeze DSW Tamil - base
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_0 ta dataset. It achieves the following results on the evaluation set:
- Loss: 0.375
- Wer: 21.4071
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: 32
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1698 | 0.1 | 100 | 0.5723 | 30.4406 |
| 0.3578 | 0.2 | 200 | 0.4302 | 25.6862 |
| 0.2832 | 0.3 | 300 | 0.3967 | 23.2048 |
| 0.2663 | 0.4 | 400 | 0.4038 | 23.8525 |
| 0.5175 | 0.5 | 500 | 0.3962 | 24.1466 |
| 0.2365 | 0.6 | 600 | 0.3850 | 22.2595 |
| 0.1692 | 0.7 | 700 | 0.3960 | 21.8687 |
| 0.1815 | 0.8 | 800 | 0.3823 | 22.0772 |
| 0.1612 | 0.9 | 900 | 0.3701 | 21.8056 |
| 0.1393 | 1.0 | 1000 | 0.375 | 21.4071 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0