wav2vec2-common_voice-tr-demo

AlbertoFor/wav2vec2-common_voice-tr-demo

wav2vec2-common_voice-tr-demo is a automatic speech recognition model from AlbertoFor. 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

22% of all-time downloads

All-time downloads

Public

Repo size

22.7 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin1.3 GB · 100%

At a glance

Task: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: wav2vec2
Access: Public
Created: May 22, 2023
Updated: May 22, 2023
SHA: 3e7c008f

Datasets

common_voice

Model card

From the Hugging Face model README

wav2vec2-common_voice-tr-demo

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:

Loss: 0.3943
Wer: 0.3340

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: 0.0003
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 15.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.23	100	3.6296	1.0
No log	0.46	200	3.1588	0.9999
No log	0.69	300	2.3111	1.0083
No log	0.92	400	0.9852	0.7981
3.6643	1.15	500	0.7056	0.7363
3.6643	1.38	600	0.6146	0.6287
3.6643	1.61	700	0.5583	0.6195
3.6643	1.84	800	0.5529	0.5678
3.6643	2.07	900	0.5280	0.5373
0.5896	2.3	1000	0.5253	0.5349
0.5896	2.53	1100	0.4803	0.5057
0.5896	2.76	1200	0.4562	0.5132
0.5896	2.99	1300	0.4252	0.4873
0.5896	3.22	1400	0.4428	0.4831
0.368	3.45	1500	0.4510	0.4779
0.368	3.68	1600	0.4404	0.4946
0.368	3.91	1700	0.4330	0.4785
0.368	4.14	1800	0.4358	0.4558
0.368	4.37	1900	0.4126	0.4643
0.2629	4.6	2000	0.4197	0.4529
0.2629	4.83	2100	0.4064	0.4409
0.2629	5.06	2200	0.4285	0.4514
0.2629	5.29	2300	0.4193	0.4204
0.2629	5.52	2400	0.4301	0.4219
0.2072	5.75	2500	0.4222	0.4335
0.2072	5.98	2600	0.4077	0.4231
0.2072	6.21	2700	0.4132	0.4121
0.2072	6.44	2800	0.4113	0.4220
0.2072	6.67	2900	0.4101	0.4175
0.1731	6.9	3000	0.4240	0.4122
0.1731	7.13	3100	0.4309	0.4023
0.1731	7.36	3200	0.4275	0.3987
0.1731	7.59	3300	0.4289	0.4063
0.1731	7.82	3400	0.4181	0.4025
0.1397	8.05	3500	0.4490	0.3885
0.1397	8.28	3600	0.4198	0.3872
0.1397	8.51	3700	0.3980	0.3842
0.1397	8.74	3800	0.4051	0.3876
0.1397	8.97	3900	0.4080	0.3912
0.1224	9.2	4000	0.4180	0.3774
0.1224	9.43	4100	0.4102	0.3820
0.1224	9.66	4200	0.3978	0.3880
0.1224	9.89	4300	0.4157	0.3731
0.1224	10.11	4400	0.4175	0.3741
0.1012	10.34	4500	0.3887	0.3705
0.1012	10.57	4600	0.4064	0.3774
0.1012	10.8	4700	0.3961	0.3622
0.1012	11.03	4800	0.3912	0.3574
0.1012	11.26	4900	0.4020	0.3638
0.088	11.49	5000	0.4117	0.3560
0.088	11.72	5100	0.3916	0.3524
0.088	11.95	5200	0.4012	0.3533
0.088	12.18	5300	0.4085	0.3584
0.088	12.41	5400	0.4000	0.3547
0.0775	12.64	5500	0.4137	0.3525
0.0775	12.87	5600	0.4005	0.3466
0.0775	13.1	5700	0.3986	0.3479
0.0775	13.33	5800	0.3983	0.3470
0.0775	13.56	5900	0.3940	0.3429
0.0716	13.79	6000	0.3872	0.3383
0.0716	14.02	6100	0.4005	0.3384
0.0716	14.25	6200	0.4005	0.3363
0.0716	14.48	6300	0.3973	0.3357
0.0716	14.71	6400	0.3957	0.3347
0.0639	14.94	6500	0.3942	0.3340

Framework versions

Transformers 4.29.2
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.11.0

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Languages: tr
Created: May 22, 2023
Updated: May 22, 2023