metadata
language:
- ml
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Tiny ml - Bharat Ramanathan
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0
type: mozilla-foundation/common_voice_11_0
config: ml
split: test
metrics:
- type: wer
value: 45.72
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: ml_in
split: test
metrics:
- type: wer
value: 62.15
name: WER
Whisper Tiny ml - Bharat Ramanathan
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1286
- Wer: 106.9296
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.5755 | 4.02 | 500 | 0.4241 | 81.2652 |
| 0.4182 | 9.01 | 1000 | 0.3245 | 72.7494 |
| 0.3387 | 14.01 | 1500 | 0.2914 | 67.2749 |
| 0.2923 | 19.0 | 2000 | 0.2745 | 60.3406 |
| 0.2596 | 24.0 | 2500 | 0.2645 | 58.2725 |
| 0.2356 | 28.02 | 3000 | 0.2629 | 60.3406 |
| 0.2167 | 33.01 | 3500 | 0.2647 | 59.9757 |
| 0.2039 | 4.02 | 4000 | 0.2617 | 58.2725 |
| 0.1938 | 9.01 | 4500 | 0.2644 | 58.2725 |
| 0.1858 | 14.01 | 5000 | 0.2636 | 58.7591 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2