|
--- |
|
language: |
|
- sw |
|
license: apache-2.0 |
|
base_model: openai/whisper-large |
|
tags: |
|
- hf-asr-leaderboard |
|
- generated_from_trainer |
|
datasets: |
|
- mozilla-foundation/common_voice_14_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper small - Denis Musinguzi |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Common Voice 14.0 |
|
type: mozilla-foundation/common_voice_14_0 |
|
config: lg |
|
split: None |
|
args: 'config: sw, split: test' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.2992427862915644 |
|
--- |
|
|
|
<!-- 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 - Denis Musinguzi |
|
|
|
This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Common Voice 14.0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3365 |
|
- Wer: 0.2992 |
|
- Cer: 0.0886 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- 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: 10000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:------:|:---------------:|:------:| |
|
| 1.1439 | 0.3 | 800 | 0.1092 | 0.5335 | 0.4676 | |
|
| 0.3861 | 0.61 | 1600 | 0.1112 | 0.4259 | 0.4185 | |
|
| 0.3195 | 0.91 | 2400 | 0.0818 | 0.3794 | 0.3365 | |
|
| 0.2447 | 1.22 | 3200 | 0.0898 | 0.3637 | 0.3310 | |
|
| 0.2168 | 1.52 | 4000 | 0.0905 | 0.3473 | 0.3250 | |
|
| 0.2099 | 1.82 | 4800 | 0.0874 | 0.3354 | 0.3205 | |
|
| 0.1793 | 2.13 | 5600 | 0.0849 | 0.3376 | 0.3013 | |
|
| 0.1437 | 2.43 | 6400 | 0.0823 | 0.3356 | 0.2985 | |
|
| 0.14 | 2.74 | 7200 | 0.0833 | 0.3322 | 0.2953 | |
|
| 0.1351 | 3.04 | 8000 | 0.0873 | 0.3328 | 0.2979 | |
|
| 0.0994 | 3.34 | 8800 | 0.0699 | 0.3374 | 0.2838 | |
|
| 0.0986 | 3.65 | 9600 | 0.3365 | 0.2992 | 0.0886 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.1 |
|
- Pytorch 2.2.1 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.15.2 |
|
|
