This model is a fine-tuned version of openai/whisper-medium on the ERR2020, Common Voice 11.0, FLEURS dataset. It achieves the following results on the evaluation set:

Loss: 0.4288
Wer: 29.7203

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-06
train_batch_size: 32
eval_batch_size: 16
seed: 42
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
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.4018	0.1	500	0.5518	39.3951
0.2654	0.2	1000	0.4611	34.3929
0.2121	0.3	1500	0.4346	32.0582
0.1752	0.4	2000	0.4247	31.1926
0.1337	0.5	2500	0.4216	30.3364
0.1281	0.6	3000	0.4219	30.0745
0.1127	0.7	3500	0.4252	29.7388
0.1254	0.8	4000	0.4276	29.8928
0.1035	0.9	4500	0.4292	29.7634
0.1114	1.0	5000	0.4288	29.7203

Framework versions

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

rristo/whisper-medium-et

Whisper Medium et

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

rristo/
whisper-medium-et