wav2vec2-sttt – AI Model by Asim037 | AlphaNeural AI

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Asim037/
wav2vec2-sttt

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automatic-speech-recognition

[finetuned_model, lj_speech11]

generated_from_trainer

FYP/LJ-Speech1111LJ

facebook/wav2vec2-base-960h

endpoints_compatible

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SpeechT5 STT Wav2Vec2

This model is a fine-tuned version of facebook/wav2vec2-base-960h on the Lj-Speech dataset. It achieves the following results on the evaluation set:

Loss: 509.3571

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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
19536.3975	0.1376	50	8125.4639
2673.9081	0.2751	100	909.8571
1958.4278	0.4127	150	544.6085
1268.7548	0.5502	200	555.2729
1504.7081	0.6878	250	520.7637
1322.1669	0.8253	300	572.5987
1331.9734	0.9629	350	514.8672
1149.1491	1.1004	400	525.9183
1063.02	1.2380	450	511.6159
1063.2695	1.3755	500	521.9377
1037.6037	1.5131	550	511.7293
1065.5638	1.6506	600	510.2425
1025.7576	1.7882	650	506.2704
1132.412	1.9257	700	525.5427
1033.8723	2.0633	750	506.9381
1027.0328	2.2008	800	513.5829
1024.9632	2.3384	850	518.4105
1023.1637	2.4759	900	515.6079
1006.7498	2.6135	950	513.5686
1026.8645	2.7510	1000	507.8027
1026.9354	2.8886	1050	509.3571

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1