metadata
language:
- ymr
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: leenag/Malasar_Luke_Dict
results: []
leenag/Malasar_Luke_Dict
This model is a fine-tuned version of openai/whisper-small on the Spoken Bible Corpus: Malasar dataset. It achieves the following results on the evaluation set:
- Loss: 0.0316
- Wer: 35.6110
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: 16
- 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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1675 | 0.6083 | 250 | 0.0688 | 52.2824 |
| 0.0941 | 1.2165 | 500 | 0.0480 | 41.7635 |
| 0.0891 | 1.8248 | 750 | 0.0433 | 46.4417 |
| 0.0502 | 2.4331 | 1000 | 0.0403 | 40.0340 |
| 0.0606 | 3.0414 | 1250 | 0.0332 | 35.7244 |
| 0.0326 | 3.6496 | 1500 | 0.0318 | 34.3351 |
| 0.0159 | 4.2579 | 1750 | 0.0319 | 33.4562 |
| 0.0276 | 4.8662 | 2000 | 0.0316 | 35.6110 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.1+cu117
- Datasets 2.16.0
- Tokenizers 0.19.1