mt5-finetuned-summarize

This model is a fine-tuned version of google/mt5-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: nan
• Rouge1: 0.0
• Rouge2: 0.0
• Rougel: 0.0
• Rougelsum: 0.0

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 20
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
0.0	0.9875	79	nan	0.0	0.0	0.0	0.0
0.0	1.975	158	nan	0.0	0.0	0.0	0.0
0.0	2.9625	237	nan	0.0	0.0	0.0	0.0
0.0	3.95	316	nan	0.0	0.0	0.0	0.0
0.0	4.9375	395	nan	0.0	0.0	0.0	0.0
0.0	5.925	474	nan	0.0	0.0	0.0	0.0
0.0	6.9125	553	nan	0.0	0.0	0.0	0.0
0.0	7.9	632	nan	0.0	0.0	0.0	0.0
0.0	8.8875	711	nan	0.0	0.0	0.0	0.0
0.0	9.875	790	nan	0.0	0.0	0.0	0.0
0.0	10.8625	869	nan	0.0	0.0	0.0	0.0
0.0	11.85	948	nan	0.0	0.0	0.0	0.0
0.0	12.8375	1027	nan	0.0	0.0	0.0	0.0
0.0	13.825	1106	nan	0.0	0.0	0.0	0.0
0.0	14.8125	1185	nan	0.0	0.0	0.0	0.0
0.0	15.8	1264	nan	0.0	0.0	0.0	0.0
0.0	16.7875	1343	nan	0.0	0.0	0.0	0.0
0.0	17.775	1422	nan	0.0	0.0	0.0	0.0
0.0	18.7625	1501	nan	0.0	0.0	0.0	0.0
0.0	19.75	1580	nan	0.0	0.0	0.0	0.0

Framework versions

• Transformers 4.47.1
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0