---
tags:
- generated_from_trainer
model-index:
- name: plbart-base-finetuned-ut-generator
  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-base-finetuned-ut-generator

This model is a fine-tuned version of [uclanlp/plbart-base](https://huggingface.co/uclanlp/plbart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3141

## 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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3625        | 0.09  | 100  | 0.4305          |
| 0.4651        | 0.18  | 200  | 0.3991          |
| 0.4273        | 0.27  | 300  | 0.3831          |
| 0.4021        | 0.36  | 400  | 0.3722          |
| 0.4101        | 0.44  | 500  | 0.3628          |
| 0.4004        | 0.53  | 600  | 0.3550          |
| 0.3877        | 0.62  | 700  | 0.3483          |
| 0.3835        | 0.71  | 800  | 0.3431          |
| 0.4012        | 0.8   | 900  | 0.3379          |
| 0.3537        | 0.89  | 1000 | 0.3343          |
| 0.3696        | 0.98  | 1100 | 0.3308          |
| 0.3574        | 1.07  | 1200 | 0.3278          |
| 0.3474        | 1.16  | 1300 | 0.3255          |
| 0.3564        | 1.24  | 1400 | 0.3228          |
| 0.3353        | 1.33  | 1500 | 0.3210          |
| 0.3233        | 1.42  | 1600 | 0.3191          |
| 0.3799        | 1.51  | 1700 | 0.3174          |
| 0.3565        | 1.6   | 1800 | 0.3164          |
| 0.3281        | 1.69  | 1900 | 0.3156          |
| 0.3272        | 1.78  | 2000 | 0.3150          |
| 0.3559        | 1.87  | 2100 | 0.3143          |
| 0.3486        | 1.96  | 2200 | 0.3141          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2