---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: BertAbstractComp
  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. -->

# BertAbstractComp

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7130
- Accuracy: 0.8062
- Precision: 0.4972
- Recall: 0.4770
- F1: 0.4772
- Top3: 0.9490
- Top3macro: 0.7051

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Top3   | Top3macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|:---------:|
| 0.4172        | 1.0   | 1640 | 0.9578          | 0.7640   | 0.4137    | 0.3973 | 0.3969 | 0.9292 | 0.6189    |
| 0.4051        | 2.0   | 3280 | 0.7427          | 0.8024   | 0.4759    | 0.4656 | 0.4654 | 0.9430 | 0.6759    |
| 0.2359        | 3.0   | 4920 | 0.8947          | 0.8015   | 0.4735    | 0.4777 | 0.4654 | 0.9402 | 0.6772    |
| 0.1543        | 4.0   | 6560 | 0.9402          | 0.8097   | 0.4900    | 0.4890 | 0.4839 | 0.9475 | 0.7062    |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.2.1
- Tokenizers 0.19.1