metadata

license: apache-2.0
tags:
  - generated_from_trainer
  - summarization
datasets:
  - samsum
metrics:
  - rouge
widget:
  - text: >
      Olivia: Hey Carter, are you still developing that restaurant business? 
      Carter: Hi Olivia  Carter: Yes, we want to launch next month :)  Olivia:
      Next month? That's soon! Congrats :)  Carter: thanks, I'm a bit nervous
      but I seriously believe we're delivering something innovative and needed 
      Olivia: I think it's a great concept and I am sure you'll do great! 
      Olivia: I am currently involved with a new restaurant in the city centre 
      Carter: Which one? Olivia: Spicy and chilled  Carter: I heard about it :)
      Is it any good? ;)  Olivia: I love the restaurant and really like working
      there  Carter: good for you! Olivia: and here's the question - are you
      still looking for restaurant to include in your discount app?  Carter:
      sure, but I think it would be better to discuss it in person - would you
      like to meet up? Olivia: That would be great!
  - type: text
model-index:
  - name: flan-t5-base-samsum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: samsum
          type: samsum
          config: samsum
          split: test
          args: samsum
        metrics:
          - name: Rouge1
            type: rouge
            value: 46.8876
language:
  - en

flan-t5-base-samsum

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

Loss: 1.3709
Rouge1: 46.8876
Rouge2: 23.2689
Rougel: 39.5369
Rougelsum: 43.1602
Gen Len: 17.2027

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: 5e-05
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
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.4403	1.0	1842	1.3829	46.5321	23.0912	39.4008	42.8993	17.0977
1.3534	2.0	3684	1.3732	47.1111	23.4456	39.5462	43.2534	17.4554
1.2795	3.0	5526	1.3709	46.8876	23.2689	39.5369	43.1602	17.2027
1.2313	4.0	7368	1.3736	47.4418	23.701	39.9856	43.6294	17.2198
1.1934	5.0	9210	1.3772	47.4656	23.9199	40.0284	43.7039	17.3162

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2