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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-base |
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datasets: |
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- grammarly/coedit |
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tags: |
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- generated_from_trainer |
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- text-generation-inference |
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metrics: |
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- rouge |
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model-index: |
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- name: coedit-base |
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results: [] |
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language: |
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- en |
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widget: |
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- text: >- |
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Fix the grammar: When I grow up, I start to understand what he said is quite |
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right. |
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example_title: Fluency |
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- text: >- |
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Make this text coherent: Their flight is weak. They run quickly through the |
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tree canopy. |
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example_title: Coherence |
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- text: >- |
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Rewrite to make this easier to understand: A storm surge is what forecasters |
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consider a hurricane's most treacherous aspect. |
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example_title: Simplification |
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- text: 'Paraphrase this: Do you know where I was born?' |
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example_title: Paraphrase |
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- text: 'Write this more formally: omg i love that song im listening to it right now' |
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example_title: Formalize |
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- text: 'Write in a more neutral way: The authors'' exposé on nutrition studies.' |
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example_title: Neutralize |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# coedit-base |
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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). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5978 |
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- Rouge1: 60.5931 |
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- Rouge2: 48.0165 |
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- Rougel: 57.8997 |
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- Rougelsum: 57.9335 |
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- Gen Len: 16.6729 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 10 |
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- eval_batch_size: 10 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| 0.7478 | 1.0 | 6908 | 0.6452 | 59.7569 | 46.3099 | 56.4301 | 56.4464 | 16.6268 | |
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| 0.7127 | 2.0 | 13816 | 0.6086 | 60.2082 | 47.27 | 57.2356 | 57.2531 | 16.6513 | |
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| 0.7136 | 3.0 | 20724 | 0.6059 | 60.3747 | 47.6257 | 57.595 | 57.6184 | 16.6349 | |
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| 0.7038 | 4.0 | 27632 | 0.5999 | 60.5075 | 47.7856 | 57.7316 | 57.7698 | 16.6735 | |
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| 0.6911 | 5.0 | 34540 | 0.5978 | 60.5931 | 48.0165 | 57.8997 | 57.9335 | 16.6729 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.7 |
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- Tokenizers 0.15.0 |
