whisper-base-full-data-aug-v2 – AI Model by thanhduycao | AlphaNeural AI

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whisper-base-full-data-aug-v2

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whisper-base-full-data-aug-v2

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

Loss: 0.2464

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: 0.0001
train_batch_size: 16
eval_batch_size: 8
seed: 42
distributed_type: tpu
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 256
total_eval_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 5000
training_steps: 63840

Training results

Training Loss	Epoch	Step	Validation Loss
0.4006	1.57	5000	0.6323
0.2901	3.13	10000	0.4845
0.2405	4.7	15000	0.4379
0.2114	6.27	20000	0.3892
0.1892	7.83	25000	0.3610
0.1638	9.4	30000	0.3343
0.154	10.97	35000	0.3186
0.1363	12.53	40000	0.2989
0.1216	14.1	45000	0.2848
0.1087	15.67	50000	0.2718
0.0984	17.23	55000	0.2576
0.0894	18.8	60000	0.2441

Framework versions

Transformers 4.28.1
Pytorch 2.1.0a0+gitcc01568
Datasets 2.13.1
Tokenizers 0.13.3