metadata
language:
- te
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Base Te - Bharat Ramanathan
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: te_in
split: test
metrics:
- type: wer
value: 39.09
name: WER
Whisper Base Te - Bharat Ramanathan
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2455
- Wer: 42.6485
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: 96
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6341 | 0.1 | 500 | 0.3894 | 60.7108 |
| 0.349 | 0.2 | 1000 | 0.3081 | 52.0935 |
| 0.2792 | 0.3 | 1500 | 0.2874 | 49.7079 |
| 0.2433 | 0.4 | 2000 | 0.2720 | 47.5657 |
| 0.2224 | 1.06 | 2500 | 0.2632 | 45.2288 |
| 0.2058 | 1.16 | 3000 | 0.2529 | 44.3038 |
| 0.1944 | 1.26 | 3500 | 0.2519 | 44.5959 |
| 0.1869 | 1.36 | 4000 | 0.2475 | 43.7196 |
| 0.1811 | 2.03 | 4500 | 0.2451 | 43.3301 |
| 0.1775 | 2.13 | 5000 | 0.2455 | 42.6485 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2