metadata
language:
- ymr
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: leenag/Malasar_Dict
results: []
leenag/Malasar_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: 0.0136
- Wer: 6.4752
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 |
|---|---|---|---|---|
| 0.0424 | 0.64 | 250 | 0.0426 | 19.6509 |
| 0.0247 | 1.28 | 500 | 0.0276 | 12.7252 |
| 0.0184 | 1.92 | 750 | 0.0254 | 13.8514 |
| 0.0077 | 2.56 | 1000 | 0.0152 | 7.2072 |
| 0.005 | 3.21 | 1250 | 0.0139 | 6.9257 |
| 0.0032 | 3.85 | 1500 | 0.0149 | 6.9257 |
| 0.0025 | 4.49 | 1750 | 0.0145 | 6.7005 |
| 0.0009 | 5.13 | 2000 | 0.0136 | 6.4752 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.15.0