This model is a fine-tuned version of futureProofGlitch/whisper-small on the Gigaspeech dataset. It achieves the following results on the evaluation set:

Loss: 0.3078
Wer Ortho: 28.4362
Wer: 16.4524

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: 1.5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.2267	0.5	500	0.3309	29.5720	18.0966
0.2035	0.99	1000	0.3078	28.4362	16.4524

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

futureProofGlitch/whisper-small-v2

FutureProofGlitch - Whisper Small - Version 2.0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

futureProofGlitch/
whisper-small-v2