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---
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
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# coedit-base
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the [CoEdIT dataset](https://huggingface.co/datasets/grammarly/coedit).
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 |