metadata
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: BERT-politics
results: []
BERT-politics
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1916
- Precision: 0.5689
- Recall: 0.6381
- F1: 0.6015
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: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
---|---|---|---|---|---|---|
No log | 1.0 | 306 | 0.1272 | 0.5622 | 0.4986 | 0.5285 |
0.1001 | 2.0 | 612 | 0.1356 | 0.5805 | 0.5542 | 0.5670 |
0.1001 | 3.0 | 918 | 0.1803 | 0.5437 | 0.6456 | 0.5903 |
0.024 | 4.0 | 1224 | 0.1916 | 0.5689 | 0.6381 | 0.6015 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1