|
--- |
|
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 |
|
|
