sit-justin/whisper-small-test

Whisper Small Chinese MOE Response

This model is a fine-tuned version of Kathernie/whisper-small-all on the MOE Response Chinese dataset. It achieves the following results on the evaluation set:

• Loss: 0.2640
• Cer: 11.0180

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: 250
• training_steps: 2000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.2252	1.0811	200	0.2339	12.4230
0.1268	2.1622	400	0.2223	10.9194
0.056	3.2432	600	0.2242	10.8701
0.023	4.3243	800	0.2387	11.3384
0.01	5.4054	1000	0.2546	11.2645
0.0044	6.4865	1200	0.2515	11.2891
0.0028	7.5676	1400	0.2552	10.9440
0.0017	8.6486	1600	0.2623	11.2645
0.0017	9.7297	1800	0.2624	10.9933
0.001	10.8108	2000	0.2640	11.0180

Framework versions

• Transformers 4.42.3
• Pytorch 2.2.0
• Datasets 2.20.0
• Tokenizers 0.19.1