|
--- |
|
language: |
|
- bn |
|
license: apache-2.0 |
|
base_model: openai/whisper-small |
|
tags: |
|
- hf-asr-leaderboard |
|
- generated_from_trainer |
|
datasets: |
|
- bengaliAI-kaggle |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: whisper-small fintuned-0-10000-50% |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: bengaliAI-kaggle |
|
type: bengaliAI-kaggle |
|
args: 'config: bn, split: test' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 90.44179607559889 |
|
--- |
|
|
|
<!-- 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 fintuned-0-10000-50% |
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the bengaliAI-kaggle dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6193 |
|
- Wer: 90.4418 |
|
|
|
## 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: 4 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 50 |
|
- training_steps: 200 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.8424 | 0.4 | 100 | 0.7538 | 103.2021 | |
|
| 0.6195 | 0.8 | 200 | 0.6193 | 90.4418 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.0 |
|
- Datasets 2.14.4 |
|
- Tokenizers 0.13.3 |
|
|
