whisper-medium-cdsd1h-lora – AI Model by llillillil | AlphaNeural AI

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llillillil/
whisper-medium-cdsd1h-lora

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openai/whisper-medium

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whisper-medium-cdsd1h-lora

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: 0.8196
Wer: 68.7556
Cer: 42.4589

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: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.8709	1.0	559	0.9190	78.1558	48.5899
0.6026	2.0	1118	0.8174	73.1871	45.7778
0.3343	3.0	1677	0.7864	70.3223	41.8295
0.1663	4.0	2236	0.7846	68.8004	44.3636
0.0664	5.0	2795	0.8196	68.7556	42.4589

Framework versions

PEFT 0.13.2
Transformers 4.44.2
Pytorch 2.0.0+cu118
Datasets 2.19.1
Tokenizers 0.19.1