kattojuprashanth238/whisper-small-te-v6

Whisper Small Te - Prashanth Kattoju

This model is a fine-tuned version of kattojuprashanth238/whisper-small-te-v5 on the HCU ASR Telugu Corpus. It achieves the following results on the evaluation set:

• Loss: 0.2009
• Wer Ortho: 51.4451
• Wer: 15.9329

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: 4
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_steps: 50
• training_steps: 1500

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.086	2.5063	50	0.1613	65.3179	19.2872
0.0096	5.0	100	0.1647	57.8035	17.8197
0.006	7.5063	150	0.1880	55.4913	14.6751
0.0032	10.0	200	0.1541	46.8208	12.3690
0.0027	12.5063	250	0.1631	48.5549	12.1593
0.0002	15.0	300	0.1617	44.5087	11.5304
0.0005	17.5063	350	0.1965	57.8035	14.6751
0.0034	20.0	400	0.1589	49.7110	12.9979
0.0036	22.5063	450	0.1761	49.7110	12.3690
0.0106	25.0	500	0.1630	62.4277	19.9161
0.005	27.5063	550	0.1809	54.3353	14.0461
0.0021	30.0	600	0.1801	52.6012	11.5304
0.0021	32.5063	650	0.1895	53.7572	14.4654
0.0027	35.0	700	0.1576	51.4451	13.6268
0.0033	37.5063	750	0.2080	58.9595	27.0440
0.0019	40.0	800	0.1958	49.7110	15.7233
0.0001	42.5063	850	0.1851	46.8208	12.9979
0.0	45.0	900	0.1887	47.9769	13.4172
0.0	47.5063	950	0.1904	47.9769	13.4172
0.0	50.0	1000	0.1916	49.1329	12.9979
0.0	52.5063	1050	0.1929	51.4451	14.8847
0.0	55.0	1100	0.1940	50.8671	14.8847
0.0	57.5063	1150	0.1951	50.8671	15.9329
0.0	60.0	1200	0.1961	50.8671	15.9329
0.0	62.5063	1250	0.1969	51.4451	15.9329
0.0	65.0	1300	0.1978	51.4451	15.9329
0.0	67.5063	1350	0.1986	51.4451	15.9329
0.0	70.0	1400	0.1994	51.4451	15.9329
0.0	72.5063	1450	0.2002	51.4451	15.9329
0.0	75.0	1500	0.2009	51.4451	15.9329

Framework versions

• Transformers 4.48.2
• Pytorch 2.6.0
• Datasets 3.2.0
• Tokenizers 0.21.0