This model is a fine-tuned version of openai/whisper-tiny on the minds14-us (whisper-tiny) dataset. It achieves the following results on the evaluation set:

Loss: 2.4049
Wer: 0.7485
Wer Ortho: 0.7569

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: 0.0003
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 500
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Wer Ortho
1.1149	1.79	100	0.5379	0.4097	0.4176
0.1705	3.57	200	0.7637	0.5762	0.5836
0.166	5.36	300	1.2479	0.5384	0.5416
0.2409	7.14	400	1.5261	0.6765	0.6619
0.2773	8.93	500	1.8106	0.7863	0.7816
0.2715	10.71	600	2.0421	0.7739	0.7841
0.2434	12.5	700	2.2664	0.7456	0.7514
0.1979	14.29	800	2.1956	0.6983	0.7039
0.1843	16.07	900	2.3711	0.8182	0.8229
0.1555	17.86	1000	2.4049	0.7485	0.7569

Framework versions

Transformers 4.37.2
Pytorch 2.1.2
Datasets 2.16.1
Tokenizers 0.15.0

Vickyee/whisper-tiny-minds14-us

whisper-tiny-minds14-us-vickymm

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Vickyee/
whisper-tiny-minds14-us