metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: results_bert_full
results: []
results_bert_full
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4327
- Accuracy: 0.8533
- F1: 0.8517
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 450 | 0.4571 | 0.8367 | 0.7623 |
| 0.4531 | 2.0 | 900 | 0.4590 | 0.8367 | 0.7623 |
| 0.4643 | 3.0 | 1350 | 0.4480 | 0.8367 | 0.7623 |
| 0.4537 | 4.0 | 1800 | 0.4498 | 0.8367 | 0.7623 |
| 0.4508 | 5.0 | 2250 | 0.4466 | 0.8367 | 0.7623 |
| 0.4531 | 6.0 | 2700 | 0.4467 | 0.8367 | 0.7623 |
| 0.4553 | 7.0 | 3150 | 0.4498 | 0.8367 | 0.7623 |
| 0.4388 | 8.0 | 3600 | 0.4473 | 0.8367 | 0.7623 |
| 0.3981 | 9.0 | 4050 | 0.3563 | 0.8722 | 0.8472 |
| 0.2981 | 10.0 | 4500 | 0.4327 | 0.8533 | 0.8517 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0