This model is a fine-tuned version of openai/whisper-medium on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.1531
Wer: 5.5543

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: 64
eval_batch_size: 32
seed: 42
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 6000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2023	0.17	1000	0.1852	7.6354
0.1215	0.33	2000	0.1577	6.4088
0.0711	1.1	3000	0.1576	6.1324
0.0656	1.27	4000	0.1499	5.8786
0.0294	2.04	5000	0.1552	5.6234
0.0351	2.21	6000	0.1531	5.5543

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.8.1.dev0
Tokenizers 0.13.2

luigisaetta/whispermedium2plus-it

luigisaetta/whisper-medium

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

luigisaetta/
whispermedium2plus-it