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---
library_name: transformers
license: apache-2.0
base_model: j5ng/et5-typos-corrector
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: make_err_ft_results
  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. -->

# make_err_ft_results

This model is a fine-tuned version of [j5ng/et5-typos-corrector](https://huggingface.co/j5ng/et5-typos-corrector) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7980
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0
- Gen Len: 12.393

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.6767        | 0.05  | 100  | 1.7986          | 0.0    | 0.0    | 0.0    | 0.0       | 11.7733 |
| 1.8043        | 0.1   | 200  | 1.5141          | 0.0    | 0.0    | 0.0    | 0.0       | 11.96   |
| 1.5302        | 0.15  | 300  | 1.3564          | 0.0    | 0.0    | 0.0    | 0.0       | 12.1402 |
| 1.4056        | 0.2   | 400  | 1.2753          | 0.0    | 0.0    | 0.0    | 0.0       | 12.152  |
| 1.3319        | 0.25  | 500  | 1.1993          | 0.0    | 0.0    | 0.0    | 0.0       | 12.1468 |
| 1.2765        | 0.3   | 600  | 1.1429          | 0.0    | 0.0    | 0.0    | 0.0       | 12.1095 |
| 1.2172        | 0.35  | 700  | 1.1243          | 0.0    | 0.0    | 0.0    | 0.0       | 12.1418 |
| 1.1631        | 0.4   | 800  | 1.0812          | 0.0    | 0.0    | 0.0    | 0.0       | 12.138  |
| 1.1409        | 0.45  | 900  | 1.0510          | 0.0    | 0.0    | 0.0    | 0.0       | 12.1267 |
| 1.1012        | 0.5   | 1000 | 1.0116          | 0.0    | 0.0    | 0.0    | 0.0       | 12.2747 |
| 1.0973        | 0.55  | 1100 | 0.9905          | 0.0    | 0.0    | 0.0    | 0.0       | 12.358  |
| 1.0126        | 0.6   | 1200 | 0.9786          | 0.0    | 0.0    | 0.0    | 0.0       | 12.3313 |
| 1.0697        | 0.65  | 1300 | 0.9535          | 0.0    | 0.0    | 0.0    | 0.0       | 12.252  |
| 1.0192        | 0.7   | 1400 | 0.9333          | 0.0    | 0.0    | 0.0    | 0.0       | 12.2155 |
| 1.0312        | 0.75  | 1500 | 0.9366          | 0.0    | 0.0    | 0.0    | 0.0       | 12.2265 |
| 0.9608        | 0.8   | 1600 | 0.9175          | 0.0    | 0.0    | 0.0    | 0.0       | 12.2825 |
| 1.0319        | 0.85  | 1700 | 0.8935          | 0.0    | 0.0    | 0.0    | 0.0       | 12.32   |
| 1.002         | 0.9   | 1800 | 0.8972          | 0.0    | 0.0    | 0.0    | 0.0       | 12.1375 |
| 0.9787        | 0.95  | 1900 | 0.8744          | 0.0    | 0.0    | 0.0    | 0.0       | 12.2127 |
| 0.973         | 1.0   | 2000 | 0.8654          | 0.0    | 0.0    | 0.0    | 0.0       | 12.377  |
| 0.7704        | 1.05  | 2100 | 0.8659          | 0.0    | 0.0    | 0.0    | 0.0       | 12.4095 |
| 0.7728        | 1.1   | 2200 | 0.8607          | 0.0    | 0.0    | 0.0    | 0.0       | 12.4428 |
| 0.7539        | 1.15  | 2300 | 0.8510          | 0.0    | 0.0    | 0.0    | 0.0       | 12.4315 |
| 0.7358        | 1.2   | 2400 | 0.8562          | 0.0    | 0.0    | 0.0    | 0.0       | 12.3308 |
| 0.7533        | 1.25  | 2500 | 0.8423          | 0.0    | 0.0    | 0.0    | 0.0       | 12.4243 |
| 0.7437        | 1.3   | 2600 | 0.8412          | 0.0    | 0.0    | 0.0    | 0.0       | 12.395  |
| 0.7368        | 1.35  | 2700 | 0.8301          | 0.0    | 0.0    | 0.0    | 0.0       | 12.381  |
| 0.7089        | 1.4   | 2800 | 0.8304          | 0.0    | 0.0    | 0.0    | 0.0       | 12.3552 |
| 0.7399        | 1.45  | 2900 | 0.8226          | 0.0    | 0.0    | 0.0    | 0.0       | 12.423  |
| 0.7027        | 1.5   | 3000 | 0.8255          | 0.0    | 0.0    | 0.0    | 0.0       | 12.3588 |
| 0.6931        | 1.55  | 3100 | 0.8173          | 0.0    | 0.0    | 0.0    | 0.0       | 12.4135 |
| 0.7254        | 1.6   | 3200 | 0.8141          | 0.0    | 0.0    | 0.0    | 0.0       | 12.4155 |
| 0.7203        | 1.65  | 3300 | 0.8102          | 0.0    | 0.0    | 0.0    | 0.0       | 12.4065 |
| 0.676         | 1.7   | 3400 | 0.8107          | 0.0    | 0.0    | 0.0    | 0.0       | 12.3648 |
| 0.7369        | 1.75  | 3500 | 0.8021          | 0.0    | 0.0    | 0.0    | 0.0       | 12.4313 |
| 0.6942        | 1.8   | 3600 | 0.8040          | 0.0    | 0.0    | 0.0    | 0.0       | 12.3852 |
| 0.7023        | 1.85  | 3700 | 0.7997          | 0.0    | 0.0    | 0.0    | 0.0       | 12.4072 |
| 0.6866        | 1.9   | 3800 | 0.8003          | 0.0    | 0.0    | 0.0    | 0.0       | 12.3915 |
| 0.7067        | 1.95  | 3900 | 0.7985          | 0.0    | 0.0    | 0.0    | 0.0       | 12.398  |
| 0.7163        | 2.0   | 4000 | 0.7980          | 0.0    | 0.0    | 0.0    | 0.0       | 12.393  |


### Framework versions

- Transformers 4.55.1
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4