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: 0.1403
- Precision: 0.4926
- Recall: 0.5024
- F1: 0.4974
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 | 0.1222 | 0.4955 | 0.3657 | 0.4208 |
| 0.1149 | 2.0 | 612 | 0.1239 | 0.5718 | 0.3977 | 0.4691 |
| 0.1149 | 3.0 | 918 | 0.1318 | 0.5444 | 0.4797 | 0.5100 |
| 0.0534 | 4.0 | 1224 | 0.1403 | 0.4926 | 0.5024 | 0.4974 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1