metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- text-classification
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- 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: 0.1922
- Accuracy: 0.9640
- Precision: 0.926
- Recall: 0.7928
- F1: 0.8542
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
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.1639 | 1.0 | 1097 | 0.1940 | 0.9389 | 0.8762 | 0.6301 | 0.7331 |
| 0.1069 | 2.0 | 2194 | 0.1561 | 0.9608 | 0.9478 | 0.7466 | 0.8352 |
| 0.0897 | 3.0 | 3291 | 0.1922 | 0.9640 | 0.926 | 0.7928 | 0.8542 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1