B5-B4_1000_1e-5_hp-myself-2 – AI Model by lnxdx | AlphaNeural AI

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lnxdx/
B5-B4_1000_1e-5_hp-myself-2

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automatic-speech-recognition

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lnxdx/B4_1000_1e-5_hp-myself-2

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C2_1000_1e-5_hp-myself-2

This model is a fine-tuned version of lnxdx/B4_1000_1e-5_hp-myself-2 on the None dataset. It achieves the following results on the evaluation set:

Loss on ShEMO train set: 0.7065
Loss on ShEMO dev set: 0.6634
WER on ShEMO train set: 26.52
WER on ShEMO dev set: 30.87
WER on Common Voice 13 test set: 19.43

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: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.7564	0.62	100	0.6705	0.3131
0.7761	1.25	200	0.6664	0.3140
0.7722	1.88	300	0.6573	0.3137
0.7035	2.5	400	0.6627	0.3157
0.7026	3.12	500	0.6834	0.3107
0.7213	3.75	600	0.6561	0.3169
0.6996	4.38	700	0.6664	0.3096
0.7146	5.0	800	0.6593	0.3148
0.7071	5.62	900	0.6646	0.3125
0.7065	6.25	1000	0.6634	0.3107

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0