Whisper-Small-Ctejarat

makhataei/Whisper-Small-Ctejarat

Whisper-Small-Ctejarat is a automatic speech recognition model from makhataei. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

0% of all-time downloads

All-time downloads

7.8K

Public

Parameters

242M

480 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors967 MB · 99%

At a glance

Task: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: whisper
Access: Public
Created: Mar 10, 2024
Updated: Mar 25, 2024
SHA: 16332d3d

Model card

From the Hugging Face model README

Whisper Small Persian

This model is a fine-tuned version of makhataei/Whisper-Small-Ctejarat on the Ctejarat dataset. It achieves the following results on the evaluation set:

Loss: 0.0031
Wer: 13.3353

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-07
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
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
0.0032	9.52	100	0.0031	13.1328
0.0027	19.05	200	0.0031	13.0171
0.002	28.57	300	0.0031	13.0171
0.0015	38.1	400	0.0031	13.0749
0.0005	47.62	500	0.0031	13.3642
0.0003	57.14	600	0.0031	13.3353
0.0002	66.67	700	0.0031	13.3353
0.0002	76.19	800	0.0031	13.3353
0.0001	85.71	900	0.0031	13.3063
0.0001	95.24	1000	0.0031	13.3063
0.0001	104.76	1100	0.0031	13.3063
0.0001	114.29	1200	0.0031	13.3931
0.0001	123.81	1300	0.0031	13.3931
0.0001	133.33	1400	0.0031	13.3642
0.0001	142.86	1500	0.0031	13.3931
0.0001	152.38	1600	0.0031	13.3931
0.0001	161.9	1700	0.0031	13.3642
0.0	171.43	1800	0.0031	13.3642
0.0001	180.95	1900	0.0031	13.3642
0.0	190.48	2000	0.0031	13.3642
0.0	200.0	2100	0.0031	13.3642
0.0	209.52	2200	0.0031	13.3642
0.0	219.05	2300	0.0031	13.3642
0.0	228.57	2400	0.0031	13.3642
0.0	238.1	2500	0.0031	13.3353
0.0	247.62	2600	0.0031	13.3353
0.0	257.14	2700	0.0031	13.3353
0.0	266.67	2800	0.0031	13.3353
0.0	276.19	2900	0.0031	13.3353
0.0	285.71	3000	0.0031	13.3353
0.0	295.24	3100	0.0031	13.3353
0.0	304.76	3200	0.0031	13.3353
0.0	314.29	3300	0.0031	13.3642
0.0	323.81	3400	0.0031	13.3642
0.0	333.33	3500	0.0031	13.3642
0.0	342.86	3600	0.0031	13.3642
0.0	352.38	3700	0.0031	13.3353
0.0	361.9	3800	0.0031	13.3353
0.0	371.43	3900	0.0031	13.3353
0.0	380.95	4000	0.0031	13.3353
0.0	390.48	4100	0.0031	13.3353
0.0	400.0	4200	0.0031	13.3353
0.0	409.52	4300	0.0031	13.3353
0.0	419.05	4400	0.0031	13.3353
0.0	428.57	4500	0.0031	13.3353
0.0	438.1	4600	0.0031	13.3353
0.0	447.62	4700	0.0031	13.3353
0.0	457.14	4800	0.0031	13.3353
0.0	466.67	4900	0.0031	13.3353
0.0	476.19	5000	0.0031	13.3353

Framework versions

Transformers 4.35.2
Pytorch 2.0.1+cu117
Datasets 2.15.0
Tokenizers 0.15.0

Task: Automatic Speech Recognition
Library: transformers
Type: whisper
License: apache-2.0
Languages: fa
Created: Mar 10, 2024
Updated: Mar 25, 2024