mt5-small-synthetic-data-plus-translated-bs32ep20lr5e3

This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.3381
• Rouge1: 0.7165
• Rouge2: 0.6111
• Rougel: 0.7004
• Rougelsum: 0.7016

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: 0.0056
• train_batch_size: 32
• eval_batch_size: 32
• 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

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
0.2243	1.0	38	0.9621	0.6801	0.5630	0.6599	0.6606
0.2209	2.0	76	0.9423	0.6766	0.5707	0.6633	0.6644
0.1953	3.0	114	0.9503	0.6525	0.5271	0.6361	0.6369
0.1812	4.0	152	0.9818	0.6811	0.5742	0.6672	0.6680
0.1418	5.0	190	0.9591	0.6868	0.5781	0.6700	0.6708
0.1312	6.0	228	1.0121	0.6900	0.5842	0.6734	0.6742
0.1236	7.0	266	0.9913	0.6787	0.5689	0.6652	0.6653
0.1068	8.0	304	0.9773	0.6886	0.5781	0.6749	0.6764
0.106	9.0	342	1.0201	0.6947	0.5825	0.6798	0.6802
0.084	10.0	380	1.0865	0.6861	0.5775	0.6726	0.6738
0.0744	11.0	418	1.0310	0.6997	0.5865	0.6849	0.6861
0.0618	12.0	456	1.1647	0.7118	0.6182	0.7016	0.7020
0.0493	13.0	494	1.1808	0.7089	0.6098	0.6959	0.6970
0.0472	14.0	532	1.2040	0.7087	0.6090	0.6956	0.6965
0.0399	15.0	570	1.1293	0.7065	0.6035	0.6953	0.6965
0.0346	16.0	608	1.2286	0.7078	0.6028	0.6928	0.6940
0.0255	17.0	646	1.2970	0.7114	0.6069	0.6986	0.7001
0.0241	18.0	684	1.3016	0.7053	0.5983	0.6893	0.6904
0.0217	19.0	722	1.3315	0.7137	0.6084	0.6999	0.7008
0.0196	20.0	760	1.3381	0.7165	0.6111	0.7004	0.7016

Framework versions

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