t5-small-bueno-tfg – AI Model by PeterBanning71 | AlphaNeural AI

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t5-small-bueno-tfg

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t5-small-bueno-tfg

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

Loss: 3.3428
Rouge2 Precision: 0.0931
Rouge2 Recall: 0.0781
Rouge2 Fmeasure: 0.0848

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge2 Precision	Rouge2 Recall	Rouge2 Fmeasure
7.2339	0.27	10	4.7620	0.0453	0.0225	0.03
4.3192	0.53	20	4.0073	0.0589	0.0336	0.0427
3.9608	0.8	30	3.6537	0.0866	0.0623	0.0722
3.7992	1.07	40	3.4747	0.091	0.0708	0.0795
3.7694	1.33	50	3.3968	0.0898	0.0721	0.0799
3.5839	1.6	60	3.3600	0.0992	0.0813	0.089
3.5573	1.87	70	3.3428	0.0931	0.0781	0.0848

Framework versions

Transformers 4.27.4
Pytorch 1.13.1+cu116
Datasets 2.11.0
Tokenizers 0.13.2