---
library_name: transformers
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sciBERT-RA-Cross-Encoder
  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. -->

# sciBERT-RA-Cross-Encoder

This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4631
- Accuracy: 0.7516
- Macro F1: 0.7516
- Genuine F1: 0.7532
- Implausible F1: 0.75

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Genuine F1 | Implausible F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:----------:|:--------------:|
| 0.5645        | 1.0   | 315  | 0.5454          | 0.6799   | 0.6789   | 0.6968     | 0.661          |
| 0.5414        | 2.0   | 630  | 0.5271          | 0.7245   | 0.7238   | 0.7375     | 0.7102         |
| 0.3990        | 3.0   | 945  | 0.5617          | 0.7452   | 0.7452   | 0.7444     | 0.746          |
| 0.2856        | 4.0   | 1260 | 0.6154          | 0.7564   | 0.7553   | 0.7713     | 0.7394         |
| 0.2646        | 5.0   | 1575 | 0.8129          | 0.7564   | 0.756    | 0.7657     | 0.7463         |
| 0.1687        | 6.0   | 1890 | 1.2355          | 0.7484   | 0.748    | 0.7375     | 0.7584         |
| 0.1542        | 7.0   | 2205 | 1.2668          | 0.7484   | 0.7484   | 0.7492     | 0.7476         |
| 0.0854        | 8.0   | 2520 | 1.4631          | 0.7516   | 0.7516   | 0.7532     | 0.75           |


### Framework versions

- Transformers 5.17.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.23.2