xbilek25/whisper-small-train-basic_1000_v1.0_shuffled

basic_train_basic_test 1000 similar params: per_device_train_batch_size=16, # bylo 16 a pod tim 1 gradient_accumulation_steps=1, warmup_steps=250, max_steps=2000

This model is a fine-tuned version of openai/whisper-small on the xbilek25/basic_train_set_en_last3cs_1000 dataset. It achieves the following results on the evaluation set:

• Loss: 0.1421
• Wer: 14.5731

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: 16
• 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: 250
• training_steps: 2000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0008	7.03	500	0.1370	16.9296
0.0003	15.03	1000	0.1390	14.3956
0.0002	23.03	1500	0.1412	14.6125
0.0002	31.02	2000	0.1421	14.5731

Framework versions

• Transformers 4.37.2
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.15.2