t5-small-finetuned-acbsql – AI Model by cgallegoan | AlphaNeural AI

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t5-small-finetuned-acbsql

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t5-small-finetuned-acbsql

This model is a fine-tuned version of t5-small on the ACB SQL dataset. It achieves the following results on the evaluation set:

Loss: 0.0699
Rouge2 Precision: 0.6901
Rouge2 Recall: 0.2546
Rouge2 Fmeasure: 0.3639

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge2 Precision	Rouge2 Recall	Rouge2 Fmeasure
0.7623	1.0	155	0.3883	0.3621	0.1411	0.1985
0.3774	2.0	310	0.2040	0.5116	0.1845	0.2672
0.2693	3.0	465	0.1461	0.5462	0.1958	0.2847
0.2129	4.0	620	0.1147	0.5799	0.2135	0.3067
0.1807	5.0	775	0.0948	0.6145	0.2264	0.3242
0.1441	6.0	930	0.0847	0.6158	0.2298	0.3284
0.1361	7.0	1085	0.0785	0.6389	0.2358	0.3371
0.1268	8.0	1240	0.0733	0.6867	0.254	0.3628
0.1259	9.0	1395	0.0709	0.6875	0.2538	0.3626
0.1199	10.0	1550	0.0699	0.6901	0.2546	0.3639

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.12.0
Tokenizers 0.13.3