rishabhjain16/whisper_large_v2_to_myst_cmu_pf_ot100

openai/whisper-large-v2

This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1969
• Wer: 9.3970

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: 16
• eval_batch_size: 32
• 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: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.6144	0.12	500	0.2795	14.0737
0.1643	0.25	1000	0.2213	11.4916
0.2175	0.38	1500	0.2009	10.0021
0.1512	1.11	2000	0.1980	11.2632
0.1527	1.24	2500	0.1916	10.8469
0.0918	1.36	3000	0.1890	9.6498
0.047	2.1	3500	0.2034	9.4274
0.0822	2.23	4000	0.1969	9.3970

Framework versions

• Transformers 4.27.0.dev0
• Pytorch 1.13.1+cu117
• Datasets 2.9.1.dev0
• Tokenizers 0.13.2