---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: arXivEdits-intention-classifier-T5-large-coarse
  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. -->


# Checkpoints for [arXivEdits paper](https://arxiv.org/pdf/2210.15067.pdf). Please see more details at the [github repo](https://github.com/chaojiang06/arXivEdits/tree/main).



# arXivEdits-intention-classifier-T5-large-coarse

This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1871
- Accuracy: 0.8607

## 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: 5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 105  | 0.3619          | 0.3699   |
| No log        | 2.0   | 210  | 0.1750          | 0.7352   |
| No log        | 3.0   | 315  | 0.1416          | 0.7922   |
| No log        | 4.0   | 420  | 0.1225          | 0.8425   |
| 0.3579        | 5.0   | 525  | 0.1310          | 0.8516   |
| 0.3579        | 6.0   | 630  | 0.1358          | 0.8425   |
| 0.3579        | 7.0   | 735  | 0.1605          | 0.8493   |
| 0.3579        | 8.0   | 840  | 0.1871          | 0.8607   |
| 0.3579        | 9.0   | 945  | 0.1990          | 0.8516   |
| 0.054         | 10.0  | 1050 | 0.2134          | 0.8607   |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.11.0+cu113
- Datasets 1.17.0
- Tokenizers 0.11.6