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anliR2-bert-base-uncased
asun17904/anliR2-bert-base-uncased
anliR2-bert-base-uncased is a machine learning model from asun17904. 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 pytorch. The card lists the license as mit.
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Public
Updated Jan 28, 2024
Repo size
3.1 GB
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.bin438 MB · 100%
At a glance
- Library
- pytorch
- License
- mit
- Access
- Public
- Created
- Jan 27, 2024
- Updated
- Jan 28, 2024
- SHA
- 7ae3ec66
Model card
From the Hugging Face model README
Knowledge Continuity Regularized Network
Dataset: ANLI Round: None
Trainer Hyperparameters:
lr= 5e-05per_device_batch_size= 8gradient_accumulation_steps= 2weight_decay= 1e-09seed= 42
Regularization Hyperparameters
numerical stability denominator constant= 1.0lambda= 1.0alpha= 1.0beta= 1.0
Extended Logs:
| eval_loss | eval_accuracy | epoch |
|---|---|---|
| 1.176 | 0.364 | 1.0 |
| 1.142 | 0.393 | 2.0 |
| 1.140 | 0.402 | 3.0 |
| 1.143 | 0.396 | 4.0 |
| 1.125 | 0.412 | 5.0 |
| 1.152 | 0.392 | 6.0 |
| 1.134 | 0.407 | 7.0 |
| 1.140 | 0.407 | 8.0 |
| 1.128 | 0.420 | 9.0 |
| 1.145 | 0.393 | 10.0 |
| 1.117 | 0.431 | 11.0 |
| 1.122 | 0.426 | 12.0 |
| 1.111 | 0.434 | 13.0 |
| 1.130 | 0.418 | 14.0 |
| 1.122 | 0.428 | 15.0 |
| 1.115 | 0.431 | 16.0 |
| 1.110 | 0.437 | 17.0 |
| 1.104 | 0.440 | 18.0 |
| 1.094 | 0.450 | 19.0 |
Test Accuracy: 0.456
- Library
- pytorch
- License
- mit
- Languages
- en
- Created
- Jan 27, 2024
- Updated
- Jan 28, 2024