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albert-xlarge-v2-finetuned-wnli
anirudh21/albert-xlarge-v2-finetuned-wnli
albert-xlarge-v2-finetuned-wnli is a text classification model from anirudh21. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- albert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Jan 26, 2022
- SHA
- 872243a7
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Datasets
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. -->
albert-xlarge-v2-finetuned-wnli
This model is a fine-tuned version of albert-xlarge-v2 on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.6869
- Accuracy: 0.5634
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: 16
- eval_batch_size: 16
- 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 | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 40 | 0.6906 | 0.5070 |
| No log | 2.0 | 80 | 0.6869 | 0.5634 |
| No log | 3.0 | 120 | 0.6905 | 0.5352 |
| No log | 4.0 | 160 | 0.6960 | 0.4225 |
| No log | 5.0 | 200 | 0.7011 | 0.3803 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.0
- Tokenizers 0.10.3
- Task
- Text Classification
- Library
- transformers
- Type
- albert
- License
- apache-2.0
- Created
- Mar 2, 2022
- Updated
- Jan 26, 2022