|
|
--- |
|
|
library_name: transformers |
|
|
language: |
|
|
- tg |
|
|
license: mit |
|
|
base_model: openai/whisper-large-v3-turbo |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
datasets: |
|
|
- fleurs |
|
|
metrics: |
|
|
- wer |
|
|
model-index: |
|
|
- name: whisper-tajik-moar-low-lr |
|
|
results: |
|
|
- task: |
|
|
name: Automatic Speech Recognition |
|
|
type: automatic-speech-recognition |
|
|
dataset: |
|
|
name: fleurs |
|
|
type: fleurs |
|
|
config: tg_tj |
|
|
split: None |
|
|
args: tg_tj |
|
|
metrics: |
|
|
- name: Wer |
|
|
type: wer |
|
|
value: 16.43159922928709 |
|
|
--- |
|
|
|
|
|
<!-- 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-tajik-moar-low-lr |
|
|
|
|
|
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the fleurs dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.2667 |
|
|
- Wer: 16.4316 |
|
|
|
|
|
## 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: 5e-05 |
|
|
- train_batch_size: 128 |
|
|
- eval_batch_size: 64 |
|
|
- seed: 42 |
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_steps: 500 |
|
|
- num_epochs: 4 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
|
| 0.1505 | 1.0 | 704 | 0.3244 | 23.0135 | |
|
|
| 0.1011 | 2.0 | 1408 | 0.2744 | 18.8362 | |
|
|
| 0.0635 | 3.0 | 2112 | 0.2646 | 17.0636 | |
|
|
| 0.0328 | 4.0 | 2816 | 0.2667 | 16.4316 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.52.4 |
|
|
- Pytorch 2.7.1+cu126 |
|
|
- Datasets 3.6.0 |
|
|
- Tokenizers 0.21.4 |
|
|
|
