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metadata
license: apache-2.0
library_name: peft
tags:
  - summarization
  - generated_from_trainer
datasets:
  - cnn_dailymail
metrics:
  - rouge
base_model: google/flan-t5-base
model-index:
  - name: flan-t5-base-finetuned-QLoRA
    results: []

flan-t5-base-finetuned-QLoRA

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

  • Loss: 1.0780
  • Rouge1: 0.2435
  • Rouge2: 0.1079
  • Rougel: 0.1991
  • Rougelsum: 0.2302

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: 3e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
12.7942 1.0 250 10.7766 0.2346 0.1022 0.1834 0.2154
3.0774 2.0 500 2.5061 0.2351 0.1094 0.197 0.2204
2.1947 3.0 750 1.4702 0.2403 0.1104 0.1997 0.2261
1.7687 4.0 1000 1.2326 0.247 0.1148 0.2024 0.2307
1.4731 5.0 1250 1.1516 0.2538 0.1203 0.2074 0.2381
1.4802 6.0 1500 1.1120 0.2432 0.1102 0.1993 0.2271
1.3568 7.0 1750 1.0945 0.2427 0.1089 0.1991 0.2279
1.4054 8.0 2000 1.0843 0.2428 0.1076 0.1993 0.2293
1.3151 9.0 2250 1.0795 0.2432 0.1076 0.1991 0.2299
1.2669 10.0 2500 1.0780 0.2435 0.1079 0.1991 0.2302

Framework versions

  • PEFT 0.8.2
  • Transformers 4.37.0
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.1