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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: BertAbstractIntroduction
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. -->
# BertAbstractIntroduction
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: 0.5373
- Accuracy: 0.8527
- Precision: 0.7768
- Recall: 0.7740
- F1: 0.7724
- Top3: 0.9608
- Top3macro: 0.9355
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|:---------:|
| 0.7833 | 1.0 | 4135 | 0.7301 | 0.7864 | 0.6818 | 0.6113 | 0.6160 | 0.9290 | 0.8766 |
| 0.5357 | 2.0 | 8270 | 0.5875 | 0.8291 | 0.7464 | 0.7173 | 0.7214 | 0.9503 | 0.9119 |
| 0.3875 | 3.0 | 12405 | 0.5240 | 0.8459 | 0.7629 | 0.7541 | 0.7541 | 0.9629 | 0.9359 |
| 0.2544 | 4.0 | 16540 | 0.5292 | 0.8577 | 0.7759 | 0.7680 | 0.7705 | 0.9643 | 0.9397 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.2.1
- Tokenizers 0.19.1
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