---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: ViT-Bert_Mimic
  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. -->

# ViT-Bert_Mimic

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1692
- Rouge1: 20.3071
- Rouge2: 17.0769
- Rougel: 20.3425
- Rougelsum: 20.2544
- Gen Len: 17.62

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 250  | 0.1710          | 0.0     | 0.0     | 0.0     | 0.0       | 20.0    |
| 0.3208        | 2.0   | 500  | 0.1424          | 0.0     | 0.0     | 0.0     | 0.0       | 20.0    |
| 0.3208        | 3.0   | 750  | 0.1396          | 28.6163 | 23.3316 | 28.7485 | 28.5768   | 15.76   |
| 0.087         | 4.0   | 1000 | 0.1349          | 15.1174 | 12.3333 | 15.1103 | 15.0938   | 18.16   |
| 0.087         | 5.0   | 1250 | 0.1373          | 1.5     | 0.6667  | 1.5     | 1.5       | 19.8    |
| 0.0621        | 6.0   | 1500 | 0.1418          | 29.7634 | 24.3915 | 29.9052 | 29.7154   | 16.0    |
| 0.0621        | 7.0   | 1750 | 0.1453          | 1.0     | 1.0     | 1.0     | 1.0       | 19.92   |
| 0.0415        | 8.0   | 2000 | 0.1504          | 6.75    | 5.6667  | 6.75    | 6.75      | 19.22   |
| 0.0415        | 9.0   | 2250 | 0.1547          | 18.9444 | 16.7436 | 19.1202 | 18.9032   | 18.06   |
| 0.0254        | 10.0  | 2500 | 0.1591          | 19.2342 | 15.6667 | 19.2782 | 19.1123   | 17.44   |
| 0.0254        | 11.0  | 2750 | 0.1601          | 19.9154 | 17.3654 | 20.011  | 19.8499   | 17.91   |
| 0.0147        | 12.0  | 3000 | 0.1647          | 16.9972 | 13.0769 | 16.9972 | 16.9154   | 17.96   |
| 0.0147        | 13.0  | 3250 | 0.1676          | 22.2859 | 16.9093 | 22.4548 | 22.1609   | 16.66   |
| 0.0094        | 14.0  | 3500 | 0.1684          | 20.2714 | 16.7308 | 20.4544 | 20.2507   | 17.47   |
| 0.0094        | 15.0  | 3750 | 0.1692          | 20.3071 | 17.0769 | 20.3425 | 20.2544   | 17.62   |


### Framework versions

- Transformers 4.37.1
- Pytorch 1.13.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.1