---
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