metadata

base_model: google-t5/t5-base
datasets:
  - Andyrasika/TweetSumm-tuned
library_name: peft
license: apache-2.0
metrics:
  - rouge
  - f1
  - precision
  - recall
tags:
  - generated_from_trainer
model-index:
  - name: t5-base-qlora-finetune-tweetsumm-1724817707
    results:
      - task:
          type: summarization
          name: Summarization
        dataset:
          name: Andyrasika/TweetSumm-tuned
          type: Andyrasika/TweetSumm-tuned
        metrics:
          - type: rouge
            value: 0.4708
            name: Rouge1
          - type: f1
            value: 0.8942
            name: F1
          - type: precision
            value: 0.8941
            name: Precision
          - type: recall
            value: 0.8945
            name: Recall

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