torgo-TestedSpeakerM01-finetuned

alexziweiwang/torgo-TestedSpeakerM01-finetuned

torgo-TestedSpeakerM01-finetuned is a automatic speech recognition model from alexziweiwang. Use it when you need speech turned into text. It is set up for transformers.

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

Downloads · 30 days

11% of all-time downloads

All-time downloads

Public

Repo size

2.5 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
Model type: wav2vec2
Access: Public
Created: Nov 17, 2022
Updated: Nov 17, 2022
SHA: 618286c5

Model card

From the Hugging Face model README

torgo-TestedSpeakerM01-finetuned

This model is a fine-tuned version of yongjian/wav2vec2-large-a on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3416
Wer: 0.7714

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: 0.0001
train_batch_size: 4
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: 1000
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
28.3192	0.84	500	1.5650	1.1343
0.4741	1.69	1000	0.3845	1.2286
0.4324	2.53	1500	0.3041	1.2849
0.3128	3.37	2000	0.3093	1.3337
0.2875	4.22	2500	0.2870	1.1972
0.2763	5.06	3000	0.3064	1.0553
0.2719	5.9	3500	0.2424	0.9534
0.2436	6.75	4000	0.2772	1.0163
0.2262	7.59	4500	0.2532	0.9989
0.2248	8.43	5000	0.2495	0.9133
0.2267	9.27	5500	0.2771	0.9155
0.1923	10.12	6000	0.2918	0.8862
0.1905	10.96	6500	0.2306	0.8700
0.184	11.8	7000	0.2470	0.8949
0.1747	12.65	7500	0.2411	0.8256
0.1641	13.49	8000	0.3096	0.8949
0.1783	14.33	8500	0.2523	0.8776
0.1575	15.18	9000	0.2606	0.8223
0.1658	16.02	9500	0.2713	0.8364
0.141	16.86	10000	0.2423	0.8061
0.1302	17.71	10500	0.3030	0.7952
0.1285	18.55	11000	0.2719	0.7811
0.203	19.39	11500	0.3074	0.8061
0.1198	20.24	12000	0.3035	0.8017
0.109	21.08	12500	0.3218	0.8082
0.109	21.92	13000	0.3668	0.8202
0.1114	22.77	13500	0.2767	0.8007
0.0949	23.61	14000	0.2965	0.7844
0.0955	24.45	14500	0.3319	0.7692
0.0913	25.3	15000	0.3034	0.7833
0.0912	26.14	15500	0.2944	0.7736
0.0794	26.98	16000	0.3479	0.7736
0.0818	27.82	16500	0.3524	0.7790
0.0836	28.67	17000	0.3467	0.7714
0.0878	29.51	17500	0.3406	0.7746

Framework versions

Transformers 4.23.1
Pytorch 1.12.1+cu113
Datasets 1.18.3
Tokenizers 0.13.2

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
Created: Nov 17, 2022
Updated: Nov 17, 2022