metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-uncased-finetuned
results: []
bert-base-uncased-finetuned
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: 0.1600
- Precision: 0.8614
- Recall: 0.9121
- F1: 0.8860
- Accuracy: 0.9548
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: 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 327 | 0.1504 | 0.8629 | 0.8675 | 0.8652 | 0.9512 |
| 0.2057 | 2.0 | 654 | 0.1462 | 0.8664 | 0.9034 | 0.8845 | 0.9548 |
| 0.2057 | 3.0 | 981 | 0.1600 | 0.8614 | 0.9121 | 0.8860 | 0.9548 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.0+cu118
- Datasets 2.19.1
- Tokenizers 0.15.2