Bidwill/whisper-small-sanskrit

Whisper Small Sanskrit_4 - Bidit Sadhukhan

This model is a fine-tuned version of openai/whisper-small on the load_data dataset. It achieves the following results on the evaluation set:

• Loss: 0.1193
• Wer: 27.9415

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: 2.5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 44
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 10000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1168	0.12	500	0.2069	47.5067
0.0854	0.23	1000	0.1774	43.4951
0.0766	0.35	1500	0.1659	40.7385
0.0631	0.47	2000	0.1644	39.0968
0.0629	0.58	2500	0.1379	34.7266
0.0763	0.7	3000	0.1401	35.1916
0.0515	0.82	3500	0.1343	34.8386
0.0457	0.93	4000	0.1185	31.6114
0.0302	1.05	4500	0.1315	33.1074
0.0276	1.17	5000	0.1245	31.1127
0.0234	1.28	5500	0.1265	30.9166
0.0266	1.4	6000	0.1289	30.6029
0.0186	1.52	6500	0.1230	30.1658
0.0284	1.63	7000	0.1157	29.2414
0.0182	1.75	7500	0.1125	27.6165
0.024	1.87	8000	0.1143	28.5970
0.0214	1.98	8500	0.1097	27.2972
0.0055	2.1	9000	0.1152	28.2497
0.0069	2.21	9500	0.1210	27.3364
0.0101	2.33	10000	0.1193	27.9415

Framework versions

• Transformers 4.35.0.dev0
• Pytorch 2.0.1+cu117
• Datasets 2.14.5
• Tokenizers 0.14.0