metadata
language:
- sn
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mother_tongue_complete_dataset
metrics:
- wer
model-index:
- name: mother_tongue_model_v3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mother_tongue_dataset_complete
type: mother_tongue_complete_dataset
args: 'config: sn'
metrics:
- name: Wer
type: wer
value: 0
mother_tongue_model_v3
This model is a fine-tuned version of openai/whisper-small on the mother_tongue_dataset_complete dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 0.0
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: 1
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0018 | 16.3934 | 500 | 0.0009 | 0.0 |
| 0.0001 | 32.7869 | 1000 | 0.0001 | 0.0 |
| 0.0 | 49.1803 | 1500 | 0.0001 | 0.0 |
| 0.0 | 65.5738 | 2000 | 0.0000 | 0.0 |
| 0.0 | 81.9672 | 2500 | 0.0000 | 0.0 |
| 0.0 | 98.3607 | 3000 | 0.0000 | 0.0 |
| 0.0 | 114.7541 | 3500 | 0.0000 | 0.0 |
| 0.0 | 131.1475 | 4000 | 0.0000 | 0.0 |
| 0.0 | 147.5410 | 4500 | 0.0000 | 0.0 |
| 0.0 | 163.9344 | 5000 | 0.0000 | 0.0 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1