This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 cs dataset. It achieves the following results on the evaluation set:

Loss: 0.2120
Wer: 9.0459

Model description

Fine tuned with deepspeed optimization and batch_size: 32.

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: 32
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0106	4.24	1000	0.1625	9.9888
0.0034	8.47	2000	0.1841	9.8304
0.0011	12.71	3000	0.1917	9.4031
0.0004	16.95	4000	0.2075	9.1177
0.0003	21.19	5000	0.2120	9.0459

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2

mikr/whisper-large2-czech-cv11-v2

Whisper Large-v2 Czech CV11 v2