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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: grammer_correction
results: []
---
<!-- 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. -->
# grammer_correction
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5597
- Rouge1: 72.0915
- Rouge2: 62.3018
- Rougel: 71.394
- Rougelsum: 71.4259
- Gen Len: 17.2788
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 6
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.7668 | 0.1 | 500 | 0.6242 | 71.3363 | 60.9781 | 70.5891 | 70.6201 | 17.3304 |
| 0.6709 | 0.19 | 1000 | 0.5964 | 71.6241 | 61.4598 | 70.8874 | 70.9203 | 17.3076 |
| 0.6519 | 0.29 | 1500 | 0.5821 | 71.7998 | 61.7754 | 71.0777 | 71.1094 | 17.2958 |
| 0.6391 | 0.39 | 2000 | 0.5748 | 71.9032 | 61.9596 | 71.1882 | 71.2215 | 17.2895 |
| 0.6311 | 0.48 | 2500 | 0.5684 | 71.9839 | 62.09 | 71.2714 | 71.3041 | 17.2805 |
| 0.6233 | 0.58 | 3000 | 0.5667 | 72.0308 | 62.1784 | 71.3246 | 71.3588 | 17.2816 |
| 0.6236 | 0.68 | 3500 | 0.5626 | 72.0792 | 62.2549 | 71.3753 | 71.4061 | 17.2703 |
| 0.6223 | 0.78 | 4000 | 0.5607 | 72.0838 | 62.2734 | 71.38 | 71.4126 | 17.2766 |
| 0.6157 | 0.87 | 4500 | 0.5603 | 72.0975 | 62.2993 | 71.3977 | 71.4284 | 17.2772 |
| 0.6167 | 0.97 | 5000 | 0.5597 | 72.0915 | 62.3018 | 71.394 | 71.4259 | 17.2788 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
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