---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Paper-Matcher-bert
  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. -->

# Paper-Matcher-bert

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5883
- Accuracy: 0.87
- Macro F1: 0.8699

## 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: 32
- 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
- lr_scheduler_warmup_steps: 75
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.3503        | 1.0   | 125  | 0.4379          | 0.83     | 0.8294   |
| 0.2971        | 2.0   | 250  | 0.4430          | 0.855    | 0.8549   |
| 0.2569        | 3.0   | 375  | 0.5001          | 0.87     | 0.87     |
| 0.1983        | 4.0   | 500  | 0.5181          | 0.855    | 0.8547   |
| 0.1342        | 5.0   | 625  | 0.5464          | 0.86     | 0.8598   |
| 0.1238        | 6.0   | 750  | 0.5883          | 0.87     | 0.8699   |


### Framework versions

- Transformers 5.18.0
- Pytorch 2.11.0+cu130
- Datasets 4.8.5
- Tokenizers 0.23.2