|
--- |
|
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_large_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: test |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 26.367876079171644 |
|
--- |
|
|
|
<!-- 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 large persian |
|
|
|
This model is a fine-tuned version of [anuragshas/whisper-large-v2-hi](https://huggingface.co/anuragshas/whisper-large-v2-hi) on the mozilla-foundation/common_voice_11_0 fa dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3047 |
|
- Wer: 26.3679 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- gradient_accumulation_steps: 2 |
|
- 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: 100 |
|
- training_steps: 1000 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.2948 | 0.19 | 250 | 0.4258 | 35.6023 | |
|
| 0.2443 | 0.39 | 500 | 0.3650 | 30.9747 | |
|
| 0.1956 | 0.58 | 750 | 0.3228 | 28.0196 | |
|
| 0.1715 | 0.78 | 1000 | 0.3047 | 26.3679 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.13.1+cu117 |
|
- Datasets 2.8.0 |
|
- Tokenizers 0.13.2 |
|
|
