whisper-tiny-all-audios – AI Model by breco | AlphaNeural AI

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breco/
whisper-tiny-all-audios

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automatic-speech-recognition

generated_from_trainer

openai/whisper-tiny

endpoints_compatible

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Whisper Tiny All Audios - vfranchis

This model is a fine-tuned version of openai/whisper-tiny on the All audios 1.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.0368
Wer: 1.9658

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 25
training_steps: 650
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.4661	0.05	25	0.5654	20.5212
0.2642	0.1	50	0.1588	8.6859
0.1282	0.15	75	0.1102	6.3494
0.0861	0.2	100	0.0901	4.9068
0.0652	0.25	125	0.0784	4.0738
0.0676	0.3	150	0.0695	3.4490
0.0865	0.35	175	0.0649	3.4185
0.0454	0.4	200	0.0610	3.0477
0.0517	0.45	225	0.0567	2.9664
0.0471	0.5	250	0.0548	2.8344
0.0394	0.55	275	0.0521	2.8648
0.0347	0.6	300	0.0488	2.4585
0.0596	0.65	325	0.0477	2.4483
0.0426	0.7	350	0.0452	2.7836
0.0428	0.75	375	0.0436	2.2401
0.0518	0.8	400	0.0417	2.1181
0.0379	0.85	425	0.0407	2.0928
0.0259	0.9	450	0.0399	1.9861
0.0691	0.95	475	0.0394	2.2096
0.0382	1.0	500	0.0384	2.1131
0.0311	1.05	525	0.0377	1.9810
0.0301	1.1	550	0.0375	1.9404
0.021	1.15	575	0.0371	1.9505
0.0205	1.2	600	0.0369	1.9404
0.0163	1.25	625	0.0369	1.9505
0.018	1.3	650	0.0368	1.9658

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 2.21.0
Tokenizers 0.19.1