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plbart-finetuned-unitTest-v1
yassmine/plbart-finetuned-unitTest-v1
plbart-finetuned-unitTest-v1 is a machine learning model from yassmine. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- plbart
- Access
- Public
- Created
- Jul 19, 2023
- Updated
- Jul 19, 2023
- SHA
- a3faef31
Base models
Model card
From the Hugging Face model README
<!-- 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 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
- Library
- transformers
- Type
- plbart
- Created
- Jul 19, 2023
- Updated
- Jul 19, 2023