t5-base-devices-sum-ver1

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

• Loss: 0.0935
• Rouge1: 97.2294
• Rouge2: 80.1323
• Rougel: 97.245
• Rougelsum: 97.2763
• Gen Len: 4.9507

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: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	186	0.2461	91.9436	71.232	91.9417	91.9585	4.6644
No log	2.0	372	0.1580	94.5247	76.1321	94.5044	94.5382	4.8953
0.488	3.0	558	0.1239	95.8673	78.1183	95.8862	95.8919	4.9102
0.488	4.0	744	0.1100	96.5746	78.9878	96.5848	96.5831	4.9102
0.488	5.0	930	0.1008	96.9074	79.5536	96.9143	96.9317	4.9291
0.1303	6.0	1116	0.0974	96.9274	79.6953	96.933	96.9473	4.9291
0.1303	7.0	1302	0.0969	96.8041	79.5073	96.817	96.8266	4.9271
0.1303	8.0	1488	0.0945	97.1496	79.9757	97.1529	97.1779	4.9534
0.089	9.0	1674	0.0944	97.253	80.1236	97.2619	97.2899	4.9595
0.089	10.0	1860	0.0935	97.2294	80.1323	97.245	97.2763	4.9507

Framework versions

• Transformers 4.18.0
• Pytorch 1.10.0+cu111
• Datasets 2.0.0
• Tokenizers 0.11.6