---
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
model-index:
- name: ER_new_context
  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. -->

# ER_new_context

This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4057

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2979        | 0.1   | 100  | 1.2437          |
| 1.1026        | 0.19  | 200  | 0.7365          |
| 0.7482        | 0.29  | 300  | 0.5781          |
| 0.6258        | 0.38  | 400  | 0.5159          |
| 0.5153        | 0.48  | 500  | 0.4504          |
| 0.4802        | 0.57  | 600  | 0.4455          |
| 0.4905        | 0.67  | 700  | 0.4059          |
| 0.382         | 0.76  | 800  | 0.4778          |
| 0.3728        | 0.86  | 900  | 0.3985          |
| 0.3274        | 0.96  | 1000 | 0.3982          |
| 0.3639        | 1.05  | 1100 | 0.4184          |
| 0.2881        | 1.15  | 1200 | 0.4454          |
| 0.3194        | 1.24  | 1300 | 0.3778          |
| 0.2695        | 1.34  | 1400 | 0.3957          |
| 0.2894        | 1.43  | 1500 | 0.4000          |
| 0.276         | 1.53  | 1600 | 0.3984          |
| 0.2325        | 1.62  | 1700 | 0.3627          |
| 0.2192        | 1.72  | 1800 | 0.3782          |
| 0.279         | 1.81  | 1900 | 0.4161          |
| 0.2636        | 1.91  | 2000 | 0.4026          |
| 0.2932        | 2.01  | 2100 | 0.3232          |
| 0.206         | 2.1   | 2200 | 0.3633          |
| 0.1865        | 2.2   | 2300 | 0.4019          |
| 0.1651        | 2.29  | 2400 | 0.4385          |
| 0.167         | 2.39  | 2500 | 0.4277          |
| 0.1705        | 2.48  | 2600 | 0.4083          |
| 0.2321        | 2.58  | 2700 | 0.3667          |
| 0.1912        | 2.67  | 2800 | 0.3772          |
| 0.192         | 2.77  | 2900 | 0.4032          |
| 0.1881        | 2.87  | 3000 | 0.4059          |
| 0.152         | 2.96  | 3100 | 0.4057          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2