Nielzac/t5-base-Text-To-Graph_Low_Quality

t5-base-Text-To-Graph

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

• Loss: 1.2583
• Rouge1: 15.9211
• Rouge2: 10.2439
• Rougel: 15.798
• Rougelsum: 15.8041
• Gen Len: 19.0

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	49	1.9977	8.1859	1.5645	8.0953	8.0998	18.7308
No log	2.0	98	1.7956	12.432	4.5448	12.3804	12.3753	18.7308
No log	3.0	147	1.6533	14.0438	7.0658	13.9349	13.9529	18.7308
No log	4.0	196	1.5491	14.0217	7.7529	13.9337	13.9439	18.7308
No log	5.0	245	1.4763	14.1269	8.3586	14.0359	14.0413	18.7308
No log	6.0	294	1.4205	14.5555	8.9978	14.4438	14.4472	18.7308
No log	7.0	343	1.3769	15.4286	9.6146	15.3249	15.3274	19.0
No log	8.0	392	1.3427	15.3635	9.7892	15.253	15.2568	19.0
No log	9.0	441	1.3177	15.4871	9.9136	15.36	15.371	19.0
No log	10.0	490	1.2978	15.6885	10.1232	15.5719	15.5818	19.0
1.8518	11.0	539	1.2826	15.7429	10.1854	15.6191	15.6226	19.0
1.8518	12.0	588	1.2720	15.8945	10.1937	15.7743	15.7814	19.0
1.8518	13.0	637	1.2645	15.9058	10.2142	15.7815	15.7875	19.0
1.8518	14.0	686	1.2598	15.9154	10.2352	15.7899	15.7952	19.0
1.8518	15.0	735	1.2583	15.9211	10.2439	15.798	15.8041	19.0

Framework versions

• Transformers 4.38.2
• Pytorch 2.1.0+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2