whisper_medium_to_myst_cmu_pf_ot100 – AI Model by rishabhjain16 | AlphaNeural AI

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whisper_medium_to_myst_cmu_pf_ot100

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automatic-speech-recognition

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openai/whisper-medium

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

Loss: 0.2617
Wer: 9.8915

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: 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
0.201	0.12	500	0.2391	10.8388
0.1726	1.06	1000	0.2055	11.1596
0.0984	1.18	1500	0.2025	10.4073
0.0782	2.12	2000	0.2073	10.9048
0.0301	3.05	2500	0.2261	10.1788
0.0284	3.17	3000	0.2303	10.0631
0.0153	4.11	3500	0.2513	10.4804
0.0386	5.04	4000	0.2617	9.8915

Framework versions

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