metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: UIT-VSFC-Bert-CLSModel-v3
results: []
UIT-VSFC-Bert-CLSModel-v3
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: 0.4363
- Accuracy: 0.8547
- F1: 0.5826
- Precision: 0.5694
- Recall: 0.5965
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-06
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 90 | 0.6868 | 0.7366 | 0.5079 | 0.6612 | 0.5146 |
| No log | 2.0 | 180 | 0.4750 | 0.8465 | 0.5775 | 0.5651 | 0.5929 |
| No log | 3.0 | 270 | 0.4363 | 0.8547 | 0.5826 | 0.5694 | 0.5965 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1