---
license: apache-2.0
base_model: cross-encoder/stsb-roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: ce-roberta-large
  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-roberta-large

This model is a fine-tuned version of [cross-encoder/stsb-roberta-large](https://huggingface.co/cross-encoder/stsb-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1713
- Accuracy: 0.6869
- Precision: 0.8654
- Recall: 0.6522

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|
| 0.7081        | 1.0   | 56   | 0.6788          | 0.5960   | 0.8372    | 0.5217 |
| 0.2275        | 2.0   | 112  | 0.2457          | 0.6667   | 0.8333    | 0.6522 |
| 0.2263        | 3.0   | 168  | 0.1814          | 0.5455   | 0.9286    | 0.3768 |
| 0.2249        | 4.0   | 224  | 0.1833          | 0.5657   | 0.9062    | 0.4203 |
| 0.1803        | 5.0   | 280  | 0.1999          | 0.6768   | 0.7937    | 0.7246 |
| 0.1708        | 6.0   | 336  | 0.1956          | 0.6566   | 0.8302    | 0.6377 |
| 0.2091        | 7.0   | 392  | 0.1789          | 0.5556   | 0.9310    | 0.3913 |
| 0.186         | 8.0   | 448  | 0.1845          | 0.6364   | 0.9231    | 0.5217 |
| 0.2133        | 9.0   | 504  | 0.1755          | 0.6162   | 0.9189    | 0.4928 |
| 0.1982        | 10.0  | 560  | 0.1713          | 0.6869   | 0.8654    | 0.6522 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.1
- Datasets 2.14.6
- Tokenizers 0.15.1