whisper-large_v2-asd_v1 – AI Model by slplab | AlphaNeural AI

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whisper-large_v2-asd_v1

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automatic-speech-recognition

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slplab/asd_apac

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whisper-large_v2-asd_v1

This model is a fine-tuned version of openai/whisper-large-v2 on slplab/asd_apac dataset. It achieves the following results on the validation set:

Loss: 0.8553
Wer: 78.4722

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
gradient_accumulation_steps: 8
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0617	10.53	100	0.6858	81.9444
0.004	21.05	200	0.7322	79.8611
0.0005	31.58	300	0.7923	80.5556
0.0003	42.11	400	0.8131	79.1667
0.0002	52.63	500	0.8263	76.7361
0.0002	63.16	600	0.8365	77.4306
0.0002	73.68	700	0.8451	78.4722
0.0002	84.21	800	0.8503	78.4722
0.0002	94.74	900	0.8541	78.4722
0.0002	105.26	1000	0.8553	78.4722

Test results

Loss: 0.6359
Wer: 36.6876

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.13.1
Tokenizers 0.13.3