mt5-small-qa_v2_enhanced2

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: 2.3751
• Rouge1: 0.4917
• Rouge2: 0.2836
• Rougel: 0.4906
• Rougelsum: 0.4912
• Bleu: 0.3255
• Exact Match: 0.3218

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: 0.0003
• 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

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Bleu	Exact Match
1.1634	1.0	2200	1.3132	0.4334	0.2574	0.4329	0.4338	0.2552	0.2570
0.6234	2.0	4400	1.2791	0.4561	0.2634	0.4558	0.4563	0.2652	0.2909
0.3062	3.0	6600	1.4780	0.4365	0.2557	0.4361	0.4371	0.2850	0.2773
0.2078	4.0	8800	1.6920	0.4863	0.2821	0.4857	0.4864	0.3287	0.3111
0.1334	5.0	11000	1.8055	0.4770	0.2651	0.4764	0.4768	0.2945	0.3166
0.0977	6.0	13200	1.9652	0.4644	0.2727	0.4631	0.4644	0.2904	0.2973
0.0672	7.0	15400	2.1246	0.4886	0.2766	0.4880	0.4888	0.2913	0.3198
0.0497	8.0	17600	2.2569	0.4905	0.2771	0.4901	0.4909	0.3072	0.3166
0.0344	9.0	19800	2.4042	0.4958	0.2861	0.4948	0.4958	0.3332	0.3232
0.0313	10.0	22000	2.3751	0.4917	0.2836	0.4906	0.4912	0.3255	0.3218

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.0
• Datasets 3.0.1
• Tokenizers 0.20.0