---
library_name: transformers
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sciBERT-RA-Context-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-Context-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: 0.8088
- Accuracy: 0.8608
- Macro F1: 0.8608
- Genuine F1: 0.8595
- Implausible F1: 0.862

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:----------:|:--------------:|
| 0.4080        | 1.0   | 669  | 0.3342          | 0.8698   | 0.8696   | 0.8649     | 0.8743         |
| 0.3192        | 2.0   | 1338 | 0.3226          | 0.8653   | 0.8653   | 0.8653     | 0.8653         |
| 0.2567        | 3.0   | 2007 | 0.3989          | 0.8608   | 0.8608   | 0.8614     | 0.8602         |
| 0.2252        | 4.0   | 2676 | 0.4264          | 0.8735   | 0.8735   | 0.874      | 0.873          |
| 0.1172        | 5.0   | 3345 | 0.6592          | 0.8548   | 0.8547   | 0.8588     | 0.8505         |
| 0.0879        | 6.0   | 4014 | 0.7473          | 0.8638   | 0.8637   | 0.8598     | 0.8675         |
| 0.1181        | 7.0   | 4683 | 0.8088          | 0.8608   | 0.8608   | 0.8595     | 0.862          |


### Framework versions

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