t5-small-herblabels

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

• Loss: 0.4823
• Rouge1: 3.0759
• Rouge2: 1.0495
• Rougel: 3.0758
• Rougelsum: 3.0431
• Gen Len: 18.9716

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: 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
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	264	1.6010	2.4276	0.5658	2.3546	2.3099	18.9091
2.5052	2.0	528	1.0237	2.9016	0.3395	2.8221	2.783	18.9673
2.5052	3.0	792	0.7793	2.962	0.3091	2.9375	2.8786	18.9588
1.1552	4.0	1056	0.6530	2.98	0.4375	2.9584	2.8711	18.9588
1.1552	5.0	1320	0.5863	3.0023	0.5882	2.987	2.9155	18.9588
0.8659	6.0	1584	0.5428	3.0576	0.8019	3.0494	2.9989	18.9716
0.8659	7.0	1848	0.5145	3.0808	0.9476	3.0719	3.0237	18.9716
0.747	8.0	2112	0.4962	3.0748	1.0032	3.0683	3.0359	18.9716
0.747	9.0	2376	0.4856	3.0702	1.0196	3.0665	3.0328	18.9716
0.6987	10.0	2640	0.4823	3.0759	1.0495	3.0758	3.0431	18.9716

Framework versions

• Transformers 4.12.5
• Pytorch 1.10.0
• Datasets 1.16.1
• Tokenizers 0.10.3