metadata
base_model: bert-base-uncased
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- f1
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: results
results: []
results
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2886
- Accuracy: 0.6
- F1: 0.5849
- Precision: 0.6185
- Recall: 0.6
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 79 | 1.2014 | 0.552 | 0.4206 | 0.7106 | 0.552 |
| 1.1506 | 2.0 | 158 | 1.0758 | 0.572 | 0.5046 | 0.6200 | 0.572 |
| 0.8847 | 3.0 | 237 | 1.0723 | 0.59 | 0.5568 | 0.5521 | 0.59 |
| 0.7512 | 4.0 | 316 | 1.0845 | 0.578 | 0.5676 | 0.6152 | 0.578 |
| 0.7512 | 5.0 | 395 | 1.1433 | 0.574 | 0.5576 | 0.5480 | 0.574 |
| 0.6091 | 6.0 | 474 | 1.2274 | 0.57 | 0.5683 | 0.5766 | 0.57 |
| 0.496 | 7.0 | 553 | 1.2917 | 0.562 | 0.5493 | 0.5634 | 0.562 |
| 0.4066 | 8.0 | 632 | 1.2886 | 0.6 | 0.5849 | 0.6185 | 0.6 |
| 0.3591 | 9.0 | 711 | 1.3574 | 0.56 | 0.5592 | 0.5768 | 0.56 |
| 0.3591 | 10.0 | 790 | 1.3527 | 0.566 | 0.5590 | 0.5706 | 0.566 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1