|
--- |
|
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 |
|
|
