BERT-Libertarian / README.md
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---
license: apache-2.0
base_model: bert-base-cased
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 [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Precision: 0.6101
- Recall: 0.6414
- F1: 0.6254
## 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 | 302 | nan | 0.6213 | 0.4303 | 0.5085 |
| 0.0 | 2.0 | 604 | nan | 0.6480 | 0.5338 | 0.5854 |
| 0.0 | 3.0 | 906 | nan | 0.6101 | 0.6414 | 0.6254 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1