scream_tertius_dropout_replicate_test7b

This model is a fine-tuned version of openai/whisper-small on the NbAiLab/NCC_speech_all_v5 dataset. It achieves the following results on the evaluation set:

• step: 19999
• eval_loss: 0.6607
• train_loss: 0.3094
• eval_wer: 10.8709
• eval_cer: 5.1449

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: 2e-05
• lr_scheduler_type: linear
• per_device_train_batch_size: 32
• total_train_batch_size_per_node: 128
• total_train_batch_size: 1024
• total_optimization_steps: 20,000
• starting_optimization_step: None
• finishing_optimization_step: 20,000
• num_train_dataset_workers: 32
• num_hosts: 8
• total_num_training_examples: 20,480,000
• steps_per_epoch: 1314
• num_beams: 5
• dropout: True
• dropout_probability: 0.1

Training results

step	eval_loss	train_loss	eval_wer	eval_cer
0	1.3578	8.1186	156.3946	118.6999
1000	0.7538	0.9632	23.5688	9.1509
2000	0.7164	0.6653	18.2704	7.4628
3000	0.7374	0.5403	15.1340	6.4853
4000	0.7819	0.4543	13.5810	6.0368
5000	0.8360	0.4266	12.2716	5.4775
6000	0.9197	0.3941	11.6017	5.2104
7000	0.9399	0.3705	11.8149	5.3515
8000	0.7468	0.3806	11.6017	5.2104
9000	0.7944	0.3562	11.5713	5.3212
10000	0.6599	0.3563	11.1145	5.1046
11000	0.6534	0.3394	11.2972	5.3313
12000	0.5689	0.3427	11.0536	5.2708
13000	0.5633	0.3313	11.1754	5.2557
14000	0.7331	0.3278	11.4495	5.4623
15000	0.6593	0.3011	11.1754	5.1902
16000	0.6180	0.3044	11.1449	5.2356
17000	0.6761	0.3058	10.9318	5.2053
18000	0.6697	0.3154	10.8709	5.1499
19000	0.6730	0.2888	11.0231	5.2658
19999	0.6607	0.3094	10.8709	5.1449

Framework versions

• Transformers 4.30.0.dev0
• Datasets 2.12.0
• Tokenizers 0.13.3