bridze – AI Model by oceanstar | AlphaNeural AI

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oceanstar/
bridze

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0

automatic-speech-recognition

hf-asr-leaderboard

generated_from_trainer

mozilla-foundation/common_voice_13_0

openai/whisper-base

endpoints_compatible

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oceanstar-bridze

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

Loss: 0.1880
Cer: 7.3894

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000

Training results

Training Loss	Epoch	Step	Cer	Validation Loss
0.3652	0.06	500	11.3504	0.3574
0.2788	0.13	1000	9.1325	0.2645
0.2213	0.1	1500	9.3132	0.2388
0.2257	0.13	2000	8.6295	0.2194
0.1941	0.16	2500	7.5109	0.2068
0.1395	0.19	3000	7.3247	0.1969
0.1787	0.23	3500	7.5517	0.1905
0.1639	0.26	4000	7.3894	0.1880

Framework versions

Transformers 4.32.0.dev0
Pytorch 1.10.1
Datasets 2.14.2
Tokenizers 0.13.3