This model is a fine-tuned version of distil-whisper/distil-large-v3 on the common_voice_16_1 dataset. It achieves the following results on the evaluation set:

Loss: 0.6148
Wer: 0.3298

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: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 42
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
0.125	4.5	1000	0.4658	0.4300
0.0412	9.01	2000	0.5247	0.3960
0.0077	13.51	3000	0.5476	0.3535
0.0007	18.02	4000	0.5731	0.3398
0.0001	22.52	5000	0.6148	0.3298

Framework versions

Transformers 4.40.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.1

sanchit-gandhi/distil-large-v3-hi-ft

distil-whisper/distil-large-v3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sanchit-gandhi/
distil-large-v3-hi-ft