|
--- |
|
language: |
|
- fa |
|
license: apache-2.0 |
|
tags: |
|
- whisper-event |
|
- generated_from_trainer |
|
datasets: |
|
- mozilla-foundation/common_voice_11_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper small Persian |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: mozilla-foundation/common_voice_11_0 fa |
|
type: mozilla-foundation/common_voice_11_0 |
|
config: fa |
|
split: None |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 32.8995086472 |
|
--- |
|
|
|
<!-- 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 Persian |
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the mozilla-foundation/common_voice_11_0 fa dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4924 |
|
- Wer: 39.8995 |
|
|
|
## 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-06 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 4 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 64 |
|
- total_eval_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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.5533 | 1.56 | 500 | 0.7044 | 54.5499 | |
|
| 0.3951 | 3.12 | 1000 | 0.5893 | 47.5210 | |
|
| 0.3296 | 4.67 | 1500 | 0.5429 | 42.6451 | |
|
| 0.2662 | 6.23 | 2000 | 0.5223 | 40.6644 | |
|
| 0.2535 | 7.79 | 2500 | 0.5045 | 38.5304 | |
|
| 0.224 | 9.35 | 3000 | 0.5002 | 36.8822 | |
|
| 0.2204 | 10.9 | 3500 | 0.4967 | 35.3076 | |
|
| 0.2024 | 12.46 | 4000 | 0.4951 | 34.9883 | |
|
| 0.2099 | 14.02 | 4500 | 0.4921 | 34.9842 | |
|
| 0.1836 | 15.58 | 5000 | 0.4924 | 34.8995 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.13.0+cu117 |
|
- Datasets 2.7.1 |
|
- Tokenizers 0.13.2 |
|
|
