|
--- |
|
language: |
|
- hi |
|
license: apache-2.0 |
|
base_model: openai/whisper-small |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- mozilla-foundation/common_voice_16_1 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Small Tr - CV 43h large batch |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Common Voice 16.1 |
|
type: mozilla-foundation/common_voice_16_1 |
|
config: tr |
|
split: None |
|
args: 'config: tr, split: test' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 21.060292928385298 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# Whisper Small Tr - CV 43h large batch |
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2890 |
|
- Wer: 21.0603 |
|
|
|
## 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: 64 |
|
- eval_batch_size: 32 |
|
- 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: 4000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.192 | 0.73 | 500 | 0.2638 | 22.1026 | |
|
| 0.1238 | 1.46 | 1000 | 0.2492 | 21.2921 | |
|
| 0.0663 | 2.19 | 1500 | 0.2483 | 20.7799 | |
|
| 0.0656 | 2.92 | 2000 | 0.2445 | 20.3073 | |
|
| 0.0391 | 3.65 | 2500 | 0.2575 | 21.1466 | |
|
| 0.0203 | 4.38 | 3000 | 0.2744 | 20.9956 | |
|
| 0.0125 | 5.11 | 3500 | 0.2841 | 20.9597 | |
|
| 0.0096 | 5.84 | 4000 | 0.2890 | 21.0603 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.39.3 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
