metadata
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results2
results: []
results2
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4683
- Accuracy: 0.8482
- F1: 0.6825
- Precision: 0.7164
- Recall: 0.6574
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: 16
- eval_batch_size: 8
- 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 | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 252 | 0.4639 | 0.8348 | 0.6145 | 0.6840 | 0.5792 |
| 0.3911 | 2.0 | 504 | 0.4304 | 0.8438 | 0.6366 | 0.7035 | 0.5972 |
| 0.3911 | 3.0 | 756 | 0.4683 | 0.8482 | 0.6825 | 0.7164 | 0.6574 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1