---
base_model: uclanlp/plbart-base
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: plbart-finetuned-unitTest-v1
  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-v1

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: 1.4949
- 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: 1
- eval_batch_size: 1
- 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   |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.2819        | 1.0   | 918   | 0.8663          | 0.0000 |
| 0.7575        | 2.0   | 1836  | 0.8740          | 0.0000 |
| 0.6118        | 3.0   | 2754  | 0.8570          | 0.0000 |
| 0.506         | 4.0   | 3672  | 0.9254          | 0.0000 |
| 0.4114        | 5.0   | 4590  | 0.9183          | 0.0000 |
| 0.3554        | 6.0   | 5508  | 0.9901          | 0.0000 |
| 0.274         | 7.0   | 6426  | 1.0385          | 0.0000 |
| 0.248         | 8.0   | 7344  | 1.0427          | 0.0000 |
| 0.2008        | 9.0   | 8262  | 1.0427          | 0.0000 |
| 0.1883        | 10.0  | 9180  | 1.1100          | 0.0000 |
| 0.1572        | 11.0  | 10098 | 1.1253          | 0.0000 |
| 0.1349        | 12.0  | 11016 | 1.1110          | 0.0000 |
| 0.1139        | 13.0  | 11934 | 1.1399          | 0.0000 |
| 0.1012        | 14.0  | 12852 | 1.1812          | 0.0000 |
| 0.0924        | 15.0  | 13770 | 1.2108          | 0.0000 |
| 0.078         | 16.0  | 14688 | 1.2008          | 0.0000 |
| 0.0738        | 17.0  | 15606 | 1.2454          | 0.0000 |
| 0.0627        | 18.0  | 16524 | 1.2557          | 0.0000 |
| 0.0559        | 19.0  | 17442 | 1.2442          | 0.0000 |
| 0.0502        | 20.0  | 18360 | 1.2724          | 0.0000 |
| 0.0478        | 21.0  | 19278 | 1.2731          | 0.0000 |
| 0.044         | 22.0  | 20196 | 1.2850          | 0.0000 |
| 0.038         | 23.0  | 21114 | 1.2929          | 0.0000 |
| 0.0357        | 24.0  | 22032 | 1.3371          | 0.0000 |
| 0.0316        | 25.0  | 22950 | 1.3470          | 0.0000 |
| 0.0285        | 26.0  | 23868 | 1.3976          | 0.0000 |
| 0.0269        | 27.0  | 24786 | 1.3808          | 0.0000 |
| 0.0258        | 28.0  | 25704 | 1.4028          | 0.0000 |
| 0.0228        | 29.0  | 26622 | 1.4032          | 0.0000 |
| 0.0219        | 30.0  | 27540 | 1.4082          | 0.0000 |
| 0.0207        | 31.0  | 28458 | 1.4250          | 0.0000 |
| 0.0186        | 32.0  | 29376 | 1.4383          | 0.0000 |
| 0.0162        | 33.0  | 30294 | 1.4060          | 0.0000 |
| 0.0151        | 34.0  | 31212 | 1.4416          | 0.0000 |
| 0.015         | 35.0  | 32130 | 1.4397          | 0.0000 |
| 0.0146        | 36.0  | 33048 | 1.4644          | 0.0000 |
| 0.0107        | 37.0  | 33966 | 1.4560          | 0.0000 |
| 0.0116        | 38.0  | 34884 | 1.4565          | 0.0000 |
| 0.0116        | 39.0  | 35802 | 1.4707          | 0.0000 |
| 0.0105        | 40.0  | 36720 | 1.4684          | 0.0000 |
| 0.0084        | 41.0  | 37638 | 1.4776          | 0.0000 |
| 0.0098        | 42.0  | 38556 | 1.4885          | 0.0000 |
| 0.0078        | 43.0  | 39474 | 1.4916          | 0.0000 |
| 0.0071        | 44.0  | 40392 | 1.4891          | 0.0000 |
| 0.0071        | 45.0  | 41310 | 1.4883          | 0.0000 |
| 0.0071        | 46.0  | 42228 | 1.4880          | 0.0000 |
| 0.0069        | 47.0  | 43146 | 1.4867          | 0.0000 |
| 0.0068        | 48.0  | 44064 | 1.4936          | 0.0000 |
| 0.0061        | 49.0  | 44982 | 1.4943          | 0.0000 |
| 0.0062        | 50.0  | 45900 | 1.4949          | 0.0000 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3