tidy-tab-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: 3.5060
• Rouge1: 0.3341
• Rouge2: 0.1528
• Rougel: 0.3104
• Rougelsum: 0.3125
• Gen Len: 17.75

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 8
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	7	4.4385	0.1922	0.0928	0.1885	0.1862	17.9167
No log	2.0	14	4.1803	0.2265	0.1136	0.2229	0.2214	17.75
No log	3.0	21	3.9826	0.2505	0.0972	0.2495	0.2517	17.1667
No log	4.0	28	3.8140	0.3166	0.131	0.3117	0.3168	17.5
No log	5.0	35	3.6817	0.3442	0.1594	0.3194	0.3211	17.4167
No log	6.0	42	3.5924	0.3341	0.1528	0.3104	0.3125	17.75
No log	7.0	49	3.5356	0.3341	0.1528	0.3104	0.3125	17.75
No log	8.0	56	3.5060	0.3341	0.1528	0.3104	0.3125	17.75

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1