metadata
language:
- ml
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 Malayalam - base
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_16_0 ml
type: mozilla-foundation/common_voice_16_0
config: ml
split: test
args: ml
metrics:
- name: Wer
type: wer
value: 42.72474513438369
Breeze DSW Malayalam - base
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_16_0 ml dataset. It achieves the following results on the evaluation set:
- Loss: 0.6260
- Wer: 42.7247
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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3151 | 4.02 | 200 | 0.4517 | 54.5134 |
| 0.0703 | 9.02 | 400 | 0.4561 | 46.7285 |
| 0.0144 | 14.02 | 600 | 0.5625 | 43.7627 |
| 0.006 | 19.02 | 800 | 0.6260 | 42.7247 |
| 0.0024 | 24.02 | 1000 | 0.6938 | 43.0306 |
| 0.0012 | 29.02 | 1200 | 0.7354 | 44.2169 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0