kavyamanohar/Malasar_Luke

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: 0.6056
• Wer: 58.9377

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
0.1635	11.36	250	0.3183	63.2210
0.0134	22.73	500	0.4616	63.7350
0.0023	34.09	750	0.5199	59.6802
0.0004	45.45	1000	0.5627	58.5951
0.0003	56.82	1250	0.5831	59.0520
0.0002	68.18	1500	0.5959	58.9949
0.0002	79.55	1750	0.6032	59.1091
0.0002	90.91	2000	0.6056	58.9377

Framework versions

• Transformers 4.37.0.dev0
• Pytorch 2.0.1+cu117
• Datasets 2.12.0
• Tokenizers 0.15.0