whisper-base-sr-yodas – AI Model by Sagicc | AlphaNeural AI

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Sagicc/
whisper-base-sr-yodas

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automatic-speech-recognition

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openai/whisper-small

endpoints_compatible

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Whisper Small Sr Yodas

This model is a fine-tuned version of openai/whisper-small on the Yodas dataset. It achieves the following results on the evaluation set:

Loss: 0.2688
Wer Ortho: 0.3334
Wer: 0.2450

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
1.0469	0.24	500	0.4020	0.5071	0.4270
0.9924	0.49	1000	0.3401	0.4082	0.3183
0.865	0.73	1500	0.3047	0.3644	0.2776
0.8443	0.98	2000	0.2893	0.3623	0.2735
0.7377	1.22	2500	0.2817	0.3472	0.2591
0.6851	1.46	3000	0.2728	0.3348	0.2466
0.7286	1.71	3500	0.2702	0.3325	0.2444
0.7215	1.95	4000	0.2688	0.3334	0.2450

Framework versions

Transformers 4.39.3
Pytorch 2.0.1+cu117
Datasets 2.18.0
Tokenizers 0.15.1