metadata
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert-clf-biencoder-cross_entropy
results: []
bert-clf-biencoder-cross_entropy
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9632
- Accuracy: 0.6667
- F1: 0.6671
- Precision: 0.6693
- Recall: 0.6667
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: 32
- eval_batch_size: 32
- 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: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.1754 | 1.0 | 78 | 1.0595 | 0.5955 | 0.5784 | 0.5956 | 0.5955 |
| 0.8707 | 2.0 | 156 | 0.8633 | 0.6505 | 0.6425 | 0.6649 | 0.6505 |
| 0.6367 | 3.0 | 234 | 0.8300 | 0.6893 | 0.6939 | 0.7081 | 0.6893 |
| 0.5392 | 4.0 | 312 | 0.8422 | 0.6893 | 0.6903 | 0.6971 | 0.6893 |
| 0.3485 | 5.0 | 390 | 0.8752 | 0.6893 | 0.6898 | 0.6924 | 0.6893 |
| 0.2629 | 6.0 | 468 | 0.9302 | 0.6796 | 0.6797 | 0.6800 | 0.6796 |
| 0.1981 | 7.0 | 546 | 0.9632 | 0.6667 | 0.6671 | 0.6693 | 0.6667 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0