---
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: plbart-finetuned-unitTest-1000
  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. -->

# plbart-finetuned-unitTest-1000

This model is a fine-tuned version of [uclanlp/plbart-base](https://huggingface.co/uclanlp/plbart-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0000
- Bleu: 0.0000

## 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 92   | 0.9023          | 0.0000 |
| No log        | 2.0   | 184  | 0.8401          | 0.0000 |
| No log        | 3.0   | 276  | 0.8096          | 0.0000 |
| No log        | 4.0   | 368  | 0.7942          | 0.0000 |
| No log        | 5.0   | 460  | 0.7848          | 0.0000 |
| 0.943         | 6.0   | 552  | 0.7818          | 0.0000 |
| 0.943         | 7.0   | 644  | 0.7911          | 0.0000 |
| 0.943         | 8.0   | 736  | 0.7874          | 0.0000 |
| 0.943         | 9.0   | 828  | 0.7970          | 0.0000 |
| 0.943         | 10.0  | 920  | 0.8062          | 0.0000 |
| 0.5025        | 11.0  | 1012 | 0.8085          | 0.0000 |
| 0.5025        | 12.0  | 1104 | 0.8179          | 0.0000 |
| 0.5025        | 13.0  | 1196 | 0.8360          | 0.0000 |
| 0.5025        | 14.0  | 1288 | 0.8385          | 0.0000 |
| 0.5025        | 15.0  | 1380 | 0.8470          | 0.0000 |
| 0.5025        | 16.0  | 1472 | 0.8556          | 0.0000 |
| 0.3309        | 17.0  | 1564 | 0.8619          | 0.0000 |
| 0.3309        | 18.0  | 1656 | 0.8701          | 0.0000 |
| 0.3309        | 19.0  | 1748 | 0.8827          | 0.0000 |
| 0.3309        | 20.0  | 1840 | 0.8871          | 0.0000 |
| 0.3309        | 21.0  | 1932 | 0.8970          | 0.0000 |
| 0.2266        | 22.0  | 2024 | 0.8984          | 0.0000 |
| 0.2266        | 23.0  | 2116 | 0.9051          | 0.0000 |
| 0.2266        | 24.0  | 2208 | 0.9188          | 0.0000 |
| 0.2266        | 25.0  | 2300 | 0.9205          | 0.0000 |
| 0.2266        | 26.0  | 2392 | 0.9278          | 0.0000 |
| 0.2266        | 27.0  | 2484 | 0.9333          | 0.0000 |
| 0.1639        | 28.0  | 2576 | 0.9456          | 0.0000 |
| 0.1639        | 29.0  | 2668 | 0.9454          | 0.0000 |
| 0.1639        | 30.0  | 2760 | 0.9522          | 0.0000 |
| 0.1639        | 31.0  | 2852 | 0.9513          | 0.0000 |
| 0.1639        | 32.0  | 2944 | 0.9554          | 0.0000 |
| 0.1251        | 33.0  | 3036 | 0.9661          | 0.0000 |
| 0.1251        | 34.0  | 3128 | 0.9698          | 0.0000 |
| 0.1251        | 35.0  | 3220 | 0.9750          | 0.0000 |
| 0.1251        | 36.0  | 3312 | 0.9722          | 0.0000 |
| 0.1251        | 37.0  | 3404 | 0.9780          | 0.0000 |
| 0.1251        | 38.0  | 3496 | 0.9789          | 0.0000 |
| 0.1019        | 39.0  | 3588 | 0.9825          | 0.0000 |
| 0.1019        | 40.0  | 3680 | 0.9913          | 0.0000 |
| 0.1019        | 41.0  | 3772 | 0.9906          | 0.0000 |
| 0.1019        | 42.0  | 3864 | 0.9922          | 0.0000 |
| 0.1019        | 43.0  | 3956 | 0.9937          | 0.0000 |
| 0.0863        | 44.0  | 4048 | 0.9981          | 0.0000 |
| 0.0863        | 45.0  | 4140 | 0.9979          | 0.0000 |
| 0.0863        | 46.0  | 4232 | 0.9984          | 0.0000 |
| 0.0863        | 47.0  | 4324 | 0.9970          | 0.0000 |
| 0.0863        | 48.0  | 4416 | 1.0003          | 0.0000 |
| 0.0783        | 49.0  | 4508 | 0.9993          | 0.0000 |
| 0.0783        | 50.0  | 4600 | 1.0000          | 0.0000 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3