metadata
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
model-index:
- name: lex-cross-encoder-mdeberta-v3-base-5neg
results: []
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