wav2vec2LugandaASR20

Gemmar/wav2vec2LugandaASR20

wav2vec2LugandaASR20 is a automatic speech recognition model from Gemmar. 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

1% of all-time downloads

All-time downloads

254

Public

Repo size

36.6 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: Jun 28, 2023
Updated: Jun 28, 2023
SHA: 542fce2d

Datasets

common_voice_13_0

Model card

From the Hugging Face model README

wav2vec2LugandaASR20

This model is a fine-tuned version of Gemmar/wav2vec2LugandaASR on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.2393
Wer: 0.2322

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: 32
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1093	0.18	100	0.2134	0.2480
0.1141	0.36	200	0.2329	0.2724
0.1224	0.54	300	0.2560	0.2864
0.1345	0.72	400	0.2348	0.2716
0.1271	0.9	500	0.2339	0.2702
0.1232	1.08	600	0.2457	0.2806
0.1149	1.27	700	0.2372	0.2695
0.1129	1.45	800	0.2328	0.2718
0.1196	1.63	900	0.2326	0.2615
0.1185	1.81	1000	0.2249	0.2672
0.1159	1.99	1100	0.2202	0.2559
0.0933	2.17	1200	0.2302	0.2559
0.0947	2.35	1300	0.2306	0.2530
0.0941	2.53	1400	0.2325	0.2509
0.0946	2.71	1500	0.2233	0.2495
0.0949	2.89	1600	0.2320	0.2443
0.0883	3.07	1700	0.2383	0.2463
0.0783	3.25	1800	0.2386	0.2437
0.0753	3.43	1900	0.2329	0.2426
0.0772	3.62	2000	0.2317	0.2392
0.0774	3.8	2100	0.2308	0.2353
0.0764	3.98	2200	0.2293	0.2357
0.0666	4.16	2300	0.2446	0.2388
0.065	4.34	2400	0.2456	0.2359
0.0643	4.52	2500	0.2446	0.2345
0.0652	4.7	2600	0.2430	0.2325
0.0669	4.88	2700	0.2393	0.2322

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.0
Tokenizers 0.13.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Jun 28, 2023
Updated: Jun 28, 2023