|
--- |
|
language: |
|
- uz |
|
license: apache-2.0 |
|
base_model: openai/whisper-small |
|
tags: |
|
- hf-asr-leaderboard |
|
- generated_from_trainer |
|
datasets: |
|
- mozilla-foundation/common_voice_16_1 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Small Uz - Aslon Khamidov -- with Uzbek Voice dataset |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Common Voice 16.1 |
|
type: mozilla-foundation/common_voice_16_1 |
|
config: uz |
|
split: test |
|
args: 'config: uz, split: test' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 30.20491240338149 |
|
--- |
|
|
|
<!-- 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 Uz - Aslon Khamidov -- with Uzbek Voice dataset |
|
|
|
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: 0.3052 |
|
- Wer: 30.2049 |
|
|
|
## 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: 15000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:------:|:-----:|:---------------:|:-------:| |
|
| 0.4689 | 0.0210 | 1000 | 0.5616 | 48.2462 | |
|
| 0.3234 | 0.0420 | 2000 | 0.4695 | 44.8210 | |
|
| 0.3078 | 0.0630 | 3000 | 0.4184 | 38.8747 | |
|
| 0.2845 | 0.0840 | 4000 | 0.3955 | 36.2861 | |
|
| 0.2771 | 0.1050 | 5000 | 0.3720 | 35.5344 | |
|
| 0.2459 | 0.1260 | 6000 | 0.3649 | 35.9415 | |
|
| 0.2482 | 0.1470 | 7000 | 0.3499 | 34.3993 | |
|
| 0.26 | 0.1680 | 8000 | 0.3389 | 32.9183 | |
|
| 0.2128 | 0.1891 | 9000 | 0.3321 | 33.2493 | |
|
| 0.2092 | 0.2101 | 10000 | 0.3215 | 31.4973 | |
|
| 0.1942 | 0.2311 | 11000 | 0.3194 | 31.0465 | |
|
| 0.1912 | 0.2521 | 12000 | 0.3184 | 31.2850 | |
|
| 0.2199 | 0.2731 | 13000 | 0.3100 | 30.6395 | |
|
| 0.1861 | 0.2941 | 14000 | 0.3059 | 30.8667 | |
|
| 0.2344 | 0.3151 | 15000 | 0.3052 | 30.2049 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.2.0 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.19.1 |
|
|