metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
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: 2.0751
- Precision: 0.5648
- Recall: 0.5655
- Accuracy: 0.5655
- F1: 0.5649
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
---|---|---|---|---|---|---|---|
1.1943 | 1.0 | 367 | 1.1549 | 0.5341 | 0.5155 | 0.5155 | 0.5161 |
0.9064 | 2.0 | 734 | 1.1347 | 0.5568 | 0.5608 | 0.5608 | 0.5528 |
0.512 | 3.0 | 1101 | 1.4481 | 0.5636 | 0.5330 | 0.5330 | 0.5261 |
0.228 | 4.0 | 1468 | 1.7226 | 0.5633 | 0.5608 | 0.5608 | 0.5588 |
0.1355 | 5.0 | 1835 | 2.0751 | 0.5648 | 0.5655 | 0.5655 | 0.5649 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Tokenizers 0.19.1