You can deploy this model and start earning money today!

Makkoen/
whisper-large-v3-cit-do005-wd0-lr5e-06-steps2000-FULL6

Name: whisper-large-v3-cit-do005-wd0-lr5e-06-steps2000-FULL6
Availability: InStock

automatic-speech-recognition

generated_from_trainer

openai/whisper-large-v3

finetune

apache-2.0

endpoints_compatible

Views

No views yet

FULL6

This model is a fine-tuned version of openai/whisper-large-v3 on the 9712 FULL-2024-10-24 dataset. It achieves the following results on the evaluation set:

Loss: 0.3684
Wer Ortho: 20.2615
Wer: 14.4085

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: 5e-06
train_batch_size: 4
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
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: 300
training_steps: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.6536	0.3661	200	0.4514	25.3730	18.9684
0.5136	0.7323	400	0.4055	22.8309	16.6362
0.4422	1.0984	600	0.3855	21.7595	15.9420
0.3691	1.4645	800	0.3767	22.0561	15.9885
0.3633	1.8307	1000	0.3694	21.1391	15.3002
0.3282	2.1968	1200	0.3701	21.1633	15.3641
0.284	2.5629	1400	0.3657	20.5429	14.6728
0.2819	2.9291	1600	0.3640	20.4431	14.6031
0.2449	3.2952	1800	0.3672	20.4067	14.5247
0.2382	3.6613	2000	0.3684	20.2615	14.4085

Framework versions

Transformers 4.45.1
Pytorch 1.13.1+cu117
Datasets 3.0.1
Tokenizers 0.20.0

Makkoen/whisper-large-v3-cit-do005-wd0-lr5e-06-steps2000-FULL6

FULL6

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Makkoen/
whisper-large-v3-cit-do005-wd0-lr5e-06-steps2000-FULL6