whisper_large_v2_to_myst_cmu – AI Model by rishabhjain16 | AlphaNeural AI

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whisper_large_v2_to_myst_cmu

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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: 0.2381
Wer: 11.1244

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
0.3639	0.12	500	0.2512	12.9597
0.1931	0.25	1000	0.2123	12.1414
0.329	1.08	1500	0.2064	11.5818
0.097	1.21	2000	0.2050	10.9775
0.0522	2.04	2500	0.2258	10.4390
0.1026	2.17	3000	0.2201	11.7017
0.0448	3.0	3500	0.2287	10.3873
0.0455	3.13	4000	0.2381	11.1244

Framework versions

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