metadata
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert-clf-biencoder-kl_divergence
results: []
bert-clf-biencoder-kl_divergence
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9704
- Accuracy: 0.6796
- F1: 0.6805
- Precision: 0.6861
- Recall: 0.6796
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 |
|---|---|---|---|---|---|---|---|
| 1.1507 | 1.0 | 78 | 1.0456 | 0.5890 | 0.5705 | 0.5986 | 0.5890 |
| 0.8285 | 2.0 | 156 | 0.8576 | 0.6408 | 0.6321 | 0.6551 | 0.6408 |
| 0.641 | 3.0 | 234 | 0.7892 | 0.7184 | 0.7180 | 0.7193 | 0.7184 |
| 0.4958 | 4.0 | 312 | 0.8131 | 0.6828 | 0.6838 | 0.6931 | 0.6828 |
| 0.3401 | 5.0 | 390 | 0.8735 | 0.6893 | 0.6903 | 0.6960 | 0.6893 |
| 0.2407 | 6.0 | 468 | 0.9288 | 0.6828 | 0.6829 | 0.6842 | 0.6828 |
| 0.1889 | 7.0 | 546 | 0.9704 | 0.6796 | 0.6805 | 0.6861 | 0.6796 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0