This model is a fine-tuned version of openai/whisper-medium on the Multilingual LibriSpeech dataset. It achieves the following results on the evaluation set:

Loss: 0.1035
Wer: 4.0373

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: 2
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1947	0.25	1000	0.1390	5.8261
0.1226	0.5	2000	0.1224	4.9978
0.1629	0.75	3000	0.1185	4.6543
0.1916	1.0	4000	0.1035	4.0373

Framework versions

Transformers 4.25.0.dev0
Pytorch 1.12.0
Datasets 2.6.2.dev0
Tokenizers 0.12.1

sanchit-gandhi/whisper-medium-es-4k-1e-5-bs-32-filter

Whisper Small Es - Sanchit Gandhi

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sanchit-gandhi/
whisper-medium-es-4k-1e-5-bs-32-filter