README.md

metadata

library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: t5-small-finetuned-samsum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: samsum
          type: samsum
          config: samsum
          split: validation
          args: samsum
        metrics:
          - name: Rouge1
            type: rouge
            value: 38.0664

t5-small-finetuned-samsum

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

• Loss: 1.8225
• Rouge1: 38.0664
• Rouge2: 16.3092
• Rougel: 31.9662
• Rougelsum: 35.0264
• Gen Len: 14.4976

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: 2e-05
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.0656	0.9992	920	1.8225	38.0664	16.3092	31.9662	35.0264	14.4976

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.19.1