wav2vec2-large-mms-1b-all-lingala-ojpl

BrainTheos/wav2vec2-large-mms-1b-all-lingala-ojpl

wav2vec2-large-mms-1b-all-lingala-ojpl is a automatic speech recognition model from BrainTheos. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as cc-by-nc-4.0.

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

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At a glance

Task: Automatic Speech Recognition
Library: transformers
License: cc-by-nc-4.0
Model type: wav2vec2
Access: Public
Created: Jul 23, 2023
Updated: Jul 24, 2023
SHA: 27a02173

Base models

facebook/mms-1b-all

Datasets

audiofolder

Model card

From the Hugging Face model README

wav2vec2-large-mms-1b-all-lingala-ojpl

This model is a fine-tuned version of facebook/mms-1b-all on the audiofolder dataset. It achieves the following results on the evaluation set:

Loss: 0.8394
Wer: 0.2698

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: 0.001
train_batch_size: 1
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: 100
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5442	0.13	100	0.9396	0.3307
0.9882	0.27	200	0.9189	0.3389
0.5845	0.4	300	0.9322	0.3129
0.4162	0.54	400	1.0742	0.2939
0.506	0.67	500	0.9626	0.3077
0.8789	0.81	600	1.0502	0.3055
0.6166	0.94	700	0.9560	0.2984
0.4101	1.08	800	0.9520	0.2995
0.6536	1.21	900	1.1213	0.2988
0.4921	1.34	1000	1.0319	0.3010
0.856	1.48	1100	0.9514	0.3043
0.4479	1.61	1200	0.9079	0.2843
0.7249	1.75	1300	0.9612	0.2895
0.5384	1.88	1400	0.9050	0.2928
0.709	2.02	1500	0.9844	0.2735
0.6575	2.15	1600	0.9377	0.2772
0.6115	2.28	1700	0.9690	0.2876
0.3119	2.42	1800	0.9222	0.2798
0.3591	2.55	1900	0.9358	0.2783
0.3979	2.69	2000	0.9156	0.2702
0.7541	2.82	2100	0.8838	0.2761
0.81	2.96	2200	0.8460	0.2813
0.2224	3.09	2300	0.9377	0.2694
0.2338	3.23	2400	0.8870	0.2746
0.5315	3.36	2500	0.8782	0.2672
0.4045	3.49	2600	0.8811	0.2653
0.4874	3.63	2700	0.9059	0.2620
0.304	3.76	2800	0.8801	0.2690
1.4688	3.9	2900	0.8394	0.2698

Framework versions

Transformers 4.32.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.13.1
Tokenizers 0.13.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: cc-by-nc-4.0
Created: Jul 23, 2023
Updated: Jul 24, 2023