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crossencoder-marco-MiniLM-L-6-v2-refine
srmishra/crossencoder-marco-MiniLM-L-6-v2-refine
crossencoder-marco-MiniLM-L-6-v2-refine is a text classification model from srmishra. 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 22, 2024
- Updated
- Feb 22, 2024
- SHA
- e4f0add2
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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-marco-MiniLM-L-6-v2-refine
This model is a fine-tuned version of cross-encoder/ms-marco-MiniLM-L-6-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0504
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: 32
- eval_batch_size: 32
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 58.7177 | 1.0 | 63 | 37.5426 |
| 0.6125 | 2.0 | 126 | 0.4536 |
| 0.1224 | 3.0 | 189 | 0.0591 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.15.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Feb 22, 2024
- Updated
- Feb 22, 2024