dgx1_whisper_base_finetune_teacher_no_noise_mozilla_100_epochs_batch_8 – AI Model by rohitp1 | AlphaNeural AI

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dgx1_whisper_base_finetune_teacher_no_noise_mozilla_100_epochs_batch_8

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automatic-speech-recognition

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dgx1_whisper_base_finetune_teacher_no_noise_mozilla_100_epochs_batch_8

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

Loss: 0.9169
Wer: 31.4602

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: 0.001
train_batch_size: 8
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 256
total_train_batch_size: 2048
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine_with_restarts
lr_scheduler_warmup_ratio: 0.2
num_epochs: 100
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2713	14.7	500	0.7014	33.4447
0.3607	29.41	1000	0.8578	34.2037
0.0171	44.12	1500	0.9436	33.6293
0.0035	58.82	2000	0.9271	31.8954
0.0	73.53	2500	0.9195	31.5264
0.0	88.23	3000	0.9169	31.4602

Framework versions

Transformers 4.25.1
Pytorch 1.12.1
Datasets 2.8.0
Tokenizers 0.13.2