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lex-cross-encoder-mbert-5neg-no-eval
LexcentraAI/lex-cross-encoder-mbert-5neg-no-eval
lex-cross-encoder-mbert-5neg-no-eval is a machine learning model from LexcentraAI. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- May 30, 2025
- Updated
- May 31, 2025
- SHA
- 1b862071
Base models
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. -->
lex-cross-encoder-mdeberta-v3-base-5neg
This model is a fine-tuned version of microsoft/mdeberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6811
- Precision: 0.2
- Recall: 1.0
- F2: 0.5556
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: 1e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F2 |
|---|---|---|---|---|---|---|
| 0.7455 | 1.0 | 1 | 0.6810 | 0.2 | 1.0 | 0.5556 |
| 0.7455 | 2.0 | 2 | 0.6811 | 0.2 | 1.0 | 0.5556 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.15.2
- Type
- bert
- License
- mit
- Created
- May 30, 2025
- Updated
- May 31, 2025