|
--- |
|
language: |
|
- fa |
|
license: apache-2.0 |
|
base_model: openai/whisper-small |
|
tags: |
|
- hf-asr-leaderboard |
|
- generated_from_trainer |
|
datasets: |
|
- mozilla-foundation/common_voice_16_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Small Fa - Brett OConnor |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Common Voice 16.0 |
|
type: mozilla-foundation/common_voice_16_0 |
|
config: fa |
|
split: None |
|
args: 'config: fa, split: test' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 36.3317501910689 |
|
--- |
|
|
|
<!-- 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 Fa - Brett OConnor |
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3430 |
|
- Wer: 36.3318 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 8 |
|
- 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: 5000 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.2622 | 0.41 | 1000 | 0.4714 | 46.2155 | |
|
| 0.2145 | 0.81 | 2000 | 0.4000 | 42.0843 | |
|
| 0.1135 | 1.22 | 3000 | 0.3757 | 38.7570 | |
|
| 0.1198 | 1.63 | 4000 | 0.3489 | 36.7330 | |
|
| 0.0721 | 2.03 | 5000 | 0.3430 | 36.3318 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.39.1 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
