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crossencoder-ms-marco-MiniLM-L-12-v2
pjbhaumik/crossencoder-ms-marco-MiniLM-L-12-v2
crossencoder-ms-marco-MiniLM-L-12-v2 is a text classification model from pjbhaumik. 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
- bert
- Access
- Public
- Created
- Feb 19, 2024
- Updated
- Feb 19, 2024
- SHA
- da0b578f
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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. -->
crossencoder-ms-marco-MiniLM-L-12-v2
This model is a fine-tuned version of cross-encoder/ms-marco-MiniLM-L-12-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0519
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-05
- train_batch_size: 100
- eval_batch_size: 80
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 84.3752 | 1.0 | 20 | 95.6720 |
| 34.7287 | 2.0 | 40 | 37.5520 |
| 17.736 | 3.0 | 60 | 13.6402 |
| 4.518 | 4.0 | 80 | 3.1808 |
| 1.2747 | 5.0 | 100 | 1.0527 |
| 0.3802 | 6.0 | 120 | 0.2666 |
| 0.1429 | 7.0 | 140 | 0.0969 |
| 0.0894 | 8.0 | 160 | 0.0368 |
| 0.0534 | 9.0 | 180 | 0.0403 |
| 0.0382 | 10.0 | 200 | 0.0497 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.0.1
- Datasets 2.17.1
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Feb 19, 2024
- Updated
- Feb 19, 2024