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samuellimabraz/
t5-base-qlora-finetune-tweetsumm

Name: t5-base-qlora-finetune-tweetsumm
Availability: InStock

peft

safetensors

generated_from_trainer

Andyrasika/TweetSumm-tuned

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t5-base-qlora-finetune-tweetsumm-1724817707

This model is a fine-tuned version of google-t5/t5-base on the Andyrasika/TweetSumm-tuned dataset. It achieves the following results on the evaluation set:

Loss: 1.7934
Rouge1: 0.4708
Rouge2: 0.2246
Rougel: 0.3984
Rougelsum: 0.4357
Gen Len: 49.4091
F1: 0.8942
Precision: 0.8941
Recall: 0.8945

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: 0.0005
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
lr_scheduler_warmup_steps: 2
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len	F1	Precision	Recall
2.062	1.0	110	1.8472	0.4633	0.2177	0.3919	0.428	49.7273	0.8911	0.8897	0.8927
1.7853	2.0	220	1.8120	0.4633	0.2203	0.3941	0.4285	49.4273	0.8953	0.8945	0.8963
1.5952	3.0	330	1.7934	0.4708	0.2246	0.3984	0.4357	49.4091	0.8942	0.8941	0.8945

Framework versions

PEFT 0.12.1.dev0
Transformers 4.44.0
Pytorch 2.4.0
Datasets 2.21.0
Tokenizers 0.19.1

samuellimabraz/t5-base-qlora-finetune-tweetsumm

t5-base-qlora-finetune-tweetsumm-1724817707

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

samuellimabraz/
t5-base-qlora-finetune-tweetsumm