This model is a fine-tuned version of openai/whisper-small on the xbilek25/train_set_1st_1000_de_en_de dataset. It achieves the following results on the evaluation set:

Loss: 0.5705
Wer: 24.4182

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: 100
training_steps: 800
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0049	6.03	400	0.5474	24.5194
0.0022	12.05	800	0.5705	24.4182

Framework versions

Transformers 4.37.2
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.15.2

xbilek25/whisper-small-train-v3.2

basic_train_basic_test 1000 similar params: per_device_train_batch_size=32, # bylo 16 a pod tim 1 gradient_accumulation_steps=2, warmup_steps=300, max_steps=3000

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

xbilek25/
whisper-small-train-v3.2