metadata
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: BERT-Economics
results: []
BERT-Economics
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: 0.1624
- Precision: 0.5650
- Recall: 0.6107
- F1: 0.5870
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 | 0.1260 | 0.5611 | 0.4458 | 0.4968 |
0.0998 | 2.0 | 612 | 0.1254 | 0.5758 | 0.6013 | 0.5883 |
0.0998 | 3.0 | 918 | 0.1624 | 0.5650 | 0.6107 | 0.5870 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1