google-flan-t5-small-e-snli-generation-label_and_explanation-selected-b48 – AI Model by sara-nabhani | AlphaNeural AI

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sara-nabhani/
google-flan-t5-small-e-snli-generation-label_and_explanation-selected-b48

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google-flan-t5-small-e-snli-generation-label_and_explanation-selected-b48

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

Loss: 1.8720
Accuracy: 0.8622
F1: 0.8623
Bertscore F1: 0.9329
Rouge1: 0.6059
Rouge2: 0.3988
Rougel: 0.5475
Rougelsum: 0.5496
Bleu: 0.4047

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: 0.001
train_batch_size: 48
eval_batch_size: 48
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.05
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Bertscore F1	Rouge1	Rouge2	Rougel	Rougelsum	Bleu
1.5084	0.17	2000	1.7484	0.8001	0.7997	0.9271	0.5768	0.3695	0.5209	0.5229	0.3703
1.2745	0.35	4000	1.8137	0.8113	0.8110	0.9304	0.5881	0.3804	0.5305	0.5325	0.3853
1.2287	0.52	6000	1.8358	0.8392	0.8403	0.9298	0.5828	0.3747	0.5282	0.5301	0.3778
1.1964	0.7	8000	1.8432	0.8430	0.8437	0.9326	0.5974	0.3905	0.5447	0.5462	0.3998
1.1674	0.87	10000	1.8567	0.8507	0.8485	0.9310	0.5947	0.3888	0.5383	0.5402	0.3892
1.1371	1.05	12000	1.8720	0.8622	0.8623	0.9329	0.6059	0.3988	0.5475	0.5496	0.4047

Framework versions

Transformers 4.27.4
Pytorch 2.0.0+cu117
Datasets 2.11.0
Tokenizers 0.13.2