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