| --- |
| license: apache-2.0 |
| base_model: cross-encoder/ms-marco-MiniLM-L-6-v2 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| model-index: |
| - name: ce-MiniLM-L6layer |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # ce-MiniLM-L6layer |
|
|
| This model is a fine-tuned version of [cross-encoder/ms-marco-MiniLM-L-6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L-6-v2) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1559 |
| - Accuracy: 0.7273 |
| - Precision: 0.9091 |
| - Recall: 0.6349 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - 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 | Accuracy | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:| |
| | 12.9679 | 1.0 | 56 | 20.2827 | 0.6970 | 0.7797 | 0.7302 | |
| | 9.2483 | 2.0 | 112 | 12.1491 | 0.6465 | 0.7188 | 0.7302 | |
| | 1.9612 | 3.0 | 168 | 1.7406 | 0.6667 | 0.8409 | 0.5873 | |
| | 0.5046 | 4.0 | 224 | 0.4060 | 0.6061 | 0.8158 | 0.4921 | |
| | 0.3575 | 5.0 | 280 | 0.2410 | 0.6667 | 0.7885 | 0.6508 | |
| | 0.244 | 6.0 | 336 | 0.1860 | 0.6263 | 0.9062 | 0.4603 | |
| | 0.2324 | 7.0 | 392 | 0.1706 | 0.6970 | 0.9231 | 0.5714 | |
| | 0.1958 | 8.0 | 448 | 0.1873 | 0.7172 | 0.7869 | 0.7619 | |
| | 0.1687 | 9.0 | 504 | 0.1742 | 0.7778 | 0.8868 | 0.7460 | |
| | 0.1581 | 10.0 | 560 | 0.1559 | 0.7273 | 0.9091 | 0.6349 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.37.2 |
| - Pytorch 2.2.1 |
| - Datasets 2.14.6 |
| - Tokenizers 0.15.1 |
| |
