---
base_model: princeton-nlp/sup-simcse-bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: BERT-Libertarian
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# BERT-Libertarian

This model is a fine-tuned version of [princeton-nlp/sup-simcse-bert-base-uncased](https://huggingface.co/princeton-nlp/sup-simcse-bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1178
- Precision: 0.4975
- Recall: 0.6115
- F1: 0.5486

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| No log        | 1.0   | 306  | 0.0845          | 0.4897    | 0.5538 | 0.5198 |
| 0.0879        | 2.0   | 612  | 0.1011          | 0.4658    | 0.6162 | 0.5306 |
| 0.0879        | 3.0   | 918  | 0.1178          | 0.4975    | 0.6115 | 0.5486 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1