w2v2-base-pretrained_lr1e-4_at0.7_da1 – AI Model by MelanieKoe | AlphaNeural AI

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MelanieKoe/
w2v2-base-pretrained_lr1e-4_at0.7_da1

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-base

endpoints_compatible

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w2v2-base-pretrained_lr1e-4_at0.7_da1

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

Loss: 6.2022
Wer: 1.0580

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: 32
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: 60
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
18.007	4.46	250	4.3814	1.0
3.2628	8.93	500	3.8568	1.0
3.1079	13.39	750	3.9328	1.0
1.4764	17.86	1000	2.7696	1.0384
0.2321	22.32	1250	4.2808	1.0507
0.1312	26.79	1500	4.8707	1.0529
0.0793	31.25	1750	5.2587	1.0558
0.0546	35.71	2000	5.6739	1.0541
0.0401	40.18	2250	5.7379	1.0494
0.0303	44.64	2500	5.8382	1.0558
0.0255	49.11	2750	6.0859	1.0567
0.0223	53.57	3000	6.0789	1.0558
0.019	58.04	3250	6.2022	1.0580

Framework versions

Transformers 4.35.0
Pytorch 2.0.0
Datasets 2.14.6
Tokenizers 0.14.1