|
--- |
|
language: |
|
- sq |
|
license: apache-2.0 |
|
library_name: transformers |
|
tags: |
|
- generated_from_trainer |
|
base_model: openai/whisper-medium |
|
datasets: |
|
- Kushtrim/common_voice_19_sq |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Medium SQ |
|
results: |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: Common Voice 19.0 |
|
type: Kushtrim/common_voice_19_sq |
|
args: 'config: sq, split: test' |
|
metrics: |
|
- type: wer |
|
value: 7.322033898305085 |
|
name: Wer |
|
--- |
|
|
|
<!-- 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 Medium SQ |
|
|
|
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 19.0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0979 |
|
- Wer: 7.3220 |
|
|
|
## 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 |
|
- num_epochs: 4 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:------:|:----:|:---------------:|:-------:| |
|
| 0.5161 | 0.4237 | 250 | 0.4949 | 38.8136 | |
|
| 0.3207 | 0.8475 | 500 | 0.3084 | 29.4689 | |
|
| 0.1595 | 1.2712 | 750 | 0.2255 | 21.6949 | |
|
| 0.1239 | 1.6949 | 1000 | 0.1733 | 16.4859 | |
|
| 0.0488 | 2.1186 | 1250 | 0.1338 | 13.0847 | |
|
| 0.04 | 2.5424 | 1500 | 0.1188 | 10.8136 | |
|
| 0.0241 | 2.9661 | 1750 | 0.1023 | 8.7684 | |
|
| 0.0075 | 3.3898 | 2000 | 0.1022 | 8.1695 | |
|
| 0.0065 | 3.8136 | 2250 | 0.0979 | 7.3220 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 3.0.0 |
|
- Tokenizers 0.19.1 |
|
|
