meeting_summarizer_model

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

• Loss: 1.5064
• Rouge1: 0.3963
• Rouge2: 0.3304
• Rougel: 0.3861
• Rougelsum: 0.3867
• Gen Len: 19.9095

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: 1
• eval_batch_size: 1
• seed: 42
• optimizer: Use 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: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.1629	1.0	5169	1.8665	0.3882	0.3076	0.3709	0.3718	19.8167
1.9476	2.0	10338	1.7073	0.3888	0.3163	0.3753	0.3757	19.9072
1.8624	3.0	15507	1.6218	0.3918	0.323	0.3794	0.3801	19.8991
1.7311	4.0	20676	1.5701	0.3916	0.3243	0.3797	0.3805	19.9118
1.7555	5.0	25845	1.5450	0.3944	0.3288	0.3833	0.384	19.9026
1.697	6.0	31014	1.5216	0.3945	0.3283	0.3839	0.3847	19.9072
1.6965	7.0	36183	1.5090	0.3951	0.3293	0.3846	0.3853	19.9037
1.6344	8.0	41352	1.5064	0.3963	0.3304	0.3861	0.3867	19.9095

Framework versions

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