This model is a fine-tuned version of openai/whisper-small on the BrainHack ASR Test Two dataset. It achieves the following results on the evaluation set:

Loss: 0.2146
Wer: 0.0326

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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 10
training_steps: 100
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0059	13.3333	20	0.1427	0.0380
0.0003	26.6667	40	0.2099	0.0380
0.0001	40.0	60	0.2171	0.0326
0.0001	53.3333	80	0.2154	0.0326
0.0001	66.6667	100	0.2146	0.0326

Framework versions

Transformers 4.40.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

MTWD/whisper-small-test-two

Whisper Small fine tuned with comms

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MTWD/
whisper-small-test-two