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

Loss: 0.3401
Wer: 17.3873

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: 1
training_steps: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0979	1.12	500	0.2481	19.0875
0.0097	3.12	1000	0.2917	16.7763
0.0017	5.12	1500	0.3298	16.9689
0.0011	7.12	2000	0.3401	17.3873

Framework versions

Transformers 4.37.2
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.15.2

xbilek25/w-medium-lang_en-set-en-de-en_similar

TMP prvontni trenovani jazyk en, train en de en similar

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

xbilek25/
w-medium-lang_en-set-en-de-en_similar