|
--- |
|
license: apache-2.0 |
|
base_model: openai/whisper-tiny |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- PolyAI/minds14 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: whisper-small-af-ZA |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: PolyAI/minds14 |
|
type: PolyAI/minds14 |
|
config: af_za |
|
split: train+validation |
|
args: af_za |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.02925243770314193 |
|
--- |
|
|
|
<!-- 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-af-ZA |
|
|
|
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0415 |
|
- Wer Ortho: 0.0529 |
|
- Wer: 0.0293 |
|
|
|
## 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: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: constant_with_warmup |
|
- lr_scheduler_warmup_steps: 5 |
|
- training_steps: 700 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:| |
|
| 0.0054 | 1.45 | 100 | 0.0312 | 0.0449 | 0.0228 | |
|
| 0.0025 | 2.9 | 200 | 0.0345 | 0.0456 | 0.0231 | |
|
| 0.0021 | 4.35 | 300 | 0.0325 | 0.0445 | 0.0206 | |
|
| 0.0018 | 5.8 | 400 | 0.0325 | 0.0449 | 0.0202 | |
|
| 0.0033 | 7.25 | 500 | 0.0390 | 0.0905 | 0.0654 | |
|
| 0.0043 | 8.7 | 600 | 0.0415 | 0.0577 | 0.0347 | |
|
| 0.0026 | 10.14 | 700 | 0.0415 | 0.0529 | 0.0293 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.0.dev0 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.1 |
|
|
