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xlnet_regression_corrected
NLPProject2023Z/xlnet_regression_corrected
xlnet_regression_corrected is a machine learning model from NLPProject2023Z. 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
- Access
- Public
- Created
- Jan 7, 2024
- Updated
- Jan 7, 2024
- SHA
- ac78e6b7
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. -->
xlnet_regression_corrected
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3655
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: 0.0005
- train_batch_size: 25
- eval_batch_size: 25
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 160 | 0.3655 |
| No log | 2.0 | 320 | 0.3655 |
| No log | 3.0 | 480 | 0.3655 |
| 0.3548 | 4.0 | 640 | 0.3655 |
| 0.3548 | 5.0 | 800 | 0.3655 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Library
- transformers
- Created
- Jan 7, 2024
- Updated
- Jan 7, 2024