This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 16 Albanian dataset. It achieves the following results on the evaluation set:

Loss: 0.7073
Wer: 34.0530

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: 8
eval_batch_size: 8
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

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1135	4.63	500	0.6519	44.8880
0.02	9.26	1000	0.6575	39.3483
0.0075	13.89	1500	0.6073	35.6823
0.0016	18.52	2000	0.6347	34.9084
0.0008	23.15	2500	0.6484	34.9491
0.0001	27.78	3000	0.6765	34.4196
0.0001	32.41	3500	0.6897	33.9308
0.0001	37.04	4000	0.6988	34.1752
0.0001	41.67	4500	0.7048	33.9715
0.0001	46.3	5000	0.7073	34.0530

Framework versions

Transformers 4.39.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2

rishabhjain16/whisper-large-v2_to_cv_colab

Whisper large-v2 Test

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

rishabhjain16/
whisper-large-v2_to_cv_colab