metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
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: 0.2235
- Accuracy: 0.9579
- F1: 0.9579
- Precision: 0.9580
- Recall: 0.9579
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1672 | 1.0 | 543 | 0.2845 | 0.9280 | 0.9279 | 0.9329 | 0.9285 |
| 0.2139 | 2.0 | 1086 | 0.2221 | 0.9439 | 0.9439 | 0.9447 | 0.9441 |
| 0.1531 | 3.0 | 1629 | 0.2010 | 0.9523 | 0.9523 | 0.9526 | 0.9522 |
| 0.0002 | 4.0 | 2172 | 0.2235 | 0.9579 | 0.9579 | 0.9580 | 0.9579 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Tokenizers 0.19.1