README.md

metadata

license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
datasets:
  - xsum
metrics:
  - rouge
model-index:
  - name: fastSUMMARIZER-t5-small-finetuned-on-xsum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: xsum
          type: xsum
          config: default
          split: validation
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 31.3222

fastSUMMARIZER-t5-small-finetuned-on-xsum

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

• Loss: 2.2425
• Rouge1: 31.3222
• Rouge2: 10.0614
• Rougel: 25.0513
• Rougelsum: 25.0446
• Gen Len: 18.8044

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: 0.0002
• train_batch_size: 28
• eval_batch_size: 28
• seed: 42
• 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	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.5078	1.0	7288	2.2860	30.9087	9.7673	24.6951	24.6927	18.7973
2.4245	2.0	14576	2.2425	31.3222	10.0614	25.0513	25.0446	18.8044

Framework versions

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