metadata

license: apache-2.0
base_model: google/flan-t5-base
datasets:
  - grammarly/coedit
tags:
  - generated_from_trainer
  - text-generation-inference
metrics:
  - rouge
model-index:
  - name: coedit-base
    results: []
language:
  - en
widget:
  - text: >-
      Fix the grammar: When I grow up, I start to understand what he said is
      quite right.
    example_title: Fluency
  - text: >-
      Make this text coherent: Their flight is weak. They run quickly through
      the tree canopy.
    example_title: Coherence
  - text: >-
      Rewrite to make this easier to understand: A storm surge is what
      forecasters consider a hurricane's most treacherous aspect.
    example_title: Simplification
  - text: 'Paraphrase this: Do you know where I was born?'
    example_title: Paraphrase
  - text: >-
      Write this more formally: omg i love that song im listening to it right
      now
    example_title: Formalize
  - text: 'Write in a more neutral way: The authors'' exposé on nutrition studies.'
    example_title: Neutralize

coedit-base

This model is a fine-tuned version of google/flan-t5-base on the CoEdIT dataset.

It achieves the following results on the evaluation set:

Loss: 0.5978
Rouge1: 60.5931
Rouge2: 48.0165
Rougel: 57.8997
Rougelsum: 57.9335
Gen Len: 16.6729

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: 1e-05
train_batch_size: 10
eval_batch_size: 10
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
0.7478	1.0	6908	0.6452	59.7569	46.3099	56.4301	56.4464	16.6268
0.7127	2.0	13816	0.6086	60.2082	47.27	57.2356	57.2531	16.6513
0.7136	3.0	20724	0.6059	60.3747	47.6257	57.595	57.6184	16.6349
0.7038	4.0	27632	0.5999	60.5075	47.7856	57.7316	57.7698	16.6735
0.6911	5.0	34540	0.5978	60.5931	48.0165	57.8997	57.9335	16.6729

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.14.7
Tokenizers 0.15.0