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---
license: apache-2.0
base_model: google/flan-t5-small
datasets:
- grammarly/coedit
tags:
- generated_from_trainer
- text-generation-inference
metrics:
- rouge
model-index:
- name: coedit-small
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-small
This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the [CoEdIT dataset](https://huggingface.co/datasets/grammarly/coedit).
It achieves the following results on the evaluation set:
- Loss: 0.8242
- Rouge1: 58.7504
- Rouge2: 45.1374
- Rougel: 55.4161
- Rougelsum: 55.4599
- Gen Len: 16.5245
## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.9482 | 1.0 | 4317 | 0.8878 | 58.4501 | 44.2623 | 54.4468 | 54.51 | 16.5088 |
| 0.9155 | 2.0 | 8634 | 0.8485 | 58.6609 | 44.7759 | 54.9844 | 55.0503 | 16.5339 |
| 0.8964 | 3.0 | 12951 | 0.8402 | 58.712 | 44.9838 | 55.2171 | 55.2697 | 16.5251 |
| 0.9049 | 4.0 | 17268 | 0.8305 | 58.7767 | 45.1325 | 55.3955 | 55.4522 | 16.5181 |
| 0.8948 | 5.0 | 21585 | 0.8242 | 58.7504 | 45.1374 | 55.4161 | 55.4599 | 16.5245 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0 |