Vigec-V3 – AI Model by HuyenNguyen | AlphaNeural AI

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HuyenNguyen/
Vigec-V3

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text2text-generation

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text-generation-inference

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Vigec-V3

This model is a fine-tuned version of VietAI/vit5-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2522
Bleu: 84.4788
Gen Len: 9.847

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: 16
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: 500
training_steps: 10000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Gen Len
0.8764	0.0	500	0.6120	68.0114	8.4626
0.6538	0.0	1000	0.4780	76.7403	10.015
0.6234	0.01	1500	0.4207	78.1726	9.8394
0.4513	0.01	2000	0.3845	79.1939	9.8914
0.4153	0.01	2500	0.3580	80.171	9.7298
0.5129	0.01	3000	0.3381	80.8668	9.8636
0.5073	0.01	3500	0.3246	81.5543	9.81
0.4623	0.01	4000	0.3106	82.1255	9.8684
0.4444	0.02	4500	0.2973	82.5565	9.848
0.4322	0.02	5000	0.2892	82.9623	9.872
0.5029	0.02	5500	0.2803	83.3084	9.8648
0.3686	0.02	6000	0.2765	83.4828	9.8602
0.4123	0.02	6500	0.2693	83.7491	9.8432
0.3593	0.03	7000	0.2674	83.8149	9.811
0.3684	0.03	7500	0.2630	84.1745	9.8668
0.3683	0.03	8000	0.2590	84.2294	9.8412
0.3581	0.03	8500	0.2568	84.3428	9.8582
0.3769	0.03	9000	0.2527	84.4367	9.8598
0.4479	0.03	9500	0.2522	84.4749	9.847
0.2856	0.04	10000	0.2522	84.4788	9.847

Framework versions

Transformers 4.26.0
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2