metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: output
results: []
output
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: 0.7643
- Accuracy: 0.8686
- Precision: 0.8681
- Recall: 0.8686
- F1: 0.8673
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2969 | 1.0 | 505 | 0.6707 | 0.8376 | 0.8375 | 0.8376 | 0.8320 |
| 0.2567 | 2.0 | 1010 | 0.6184 | 0.8572 | 0.8516 | 0.8572 | 0.8519 |
| 0.1496 | 3.0 | 1515 | 0.6471 | 0.8693 | 0.8637 | 0.8693 | 0.8651 |
| 0.0826 | 4.0 | 2020 | 0.6897 | 0.8641 | 0.8600 | 0.8641 | 0.8604 |
| 0.0467 | 5.0 | 2525 | 0.7378 | 0.8676 | 0.8671 | 0.8676 | 0.8663 |
| 0.0229 | 6.0 | 3030 | 0.7521 | 0.8678 | 0.8670 | 0.8678 | 0.8666 |
| 0.01 | 7.0 | 3535 | 0.7643 | 0.8686 | 0.8681 | 0.8686 | 0.8673 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0