results_mt5_xl-sum – AI Model by hiba2 | AlphaNeural AI | AlphaNeural AI

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results_mt5_xl-sum

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text2text-generation

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results_mt5_xl-sum

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.8431
Rouge1 Fmeasure: 0.6139
Rouge2 Fmeasure: 0.1189
Rougel Fmeasure: 0.1997
Meteor: 0.3315
Bertscore F1: 0.8418

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: 0.0005
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 250
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1 Fmeasure	Rouge2 Fmeasure	Rougel Fmeasure	Meteor	Bertscore F1
2.6516	0.8529	500	0.9710	0.2668	0.0484	0.1537	0.2745	0.8284
1.0475	1.7058	1000	0.8792	0.4289	0.0884	0.1737	0.2949	0.8278
0.9413	2.5586	1500	0.8457	0.4960	0.0865	0.1898	0.3141	0.8339
0.8711	3.4115	2000	0.8398	0.5400	0.1121	0.1941	0.3110	0.8397
0.8235	4.2644	2500	0.8345	0.5587	0.1022	0.2041	0.3160	0.8388
0.7797	5.1173	3000	0.8368	0.5735	0.1036	0.2044	0.3157	0.8344
0.7401	5.9701	3500	0.8217	0.5507	0.1133	0.1936	0.3186	0.8366
0.7022	6.8230	4000	0.8361	0.5808	0.1118	0.2008	0.3227	0.8406
0.6796	7.6759	4500	0.8344	0.6173	0.1277	0.1986	0.3260	0.8407
0.6523	8.5288	5000	0.8436	0.6232	0.1186	0.2024	0.3317	0.8398
0.6385	9.3817	5500	0.8431	0.6139	0.1189	0.1997	0.3315	0.8418

Framework versions

Transformers 4.40.0
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1