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: 0.9480
- Accuracy: 0.6634
- F1: 0.6648
- Precision: 0.6687
- Recall: 0.6634
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 |
|---|---|---|---|---|---|---|---|
| 1.1883 | 1.0 | 78 | 1.0551 | 0.6019 | 0.5890 | 0.5964 | 0.6019 |
| 0.859 | 2.0 | 156 | 0.8377 | 0.6311 | 0.6231 | 0.6472 | 0.6311 |
| 0.6539 | 3.0 | 234 | 0.7989 | 0.6634 | 0.6651 | 0.6677 | 0.6634 |
| 0.5242 | 4.0 | 312 | 0.8181 | 0.6731 | 0.6717 | 0.6823 | 0.6731 |
| 0.3728 | 5.0 | 390 | 0.8442 | 0.6861 | 0.6855 | 0.6889 | 0.6861 |
| 0.2566 | 6.0 | 468 | 0.9040 | 0.6764 | 0.6769 | 0.6779 | 0.6764 |
| 0.1959 | 7.0 | 546 | 0.9480 | 0.6634 | 0.6648 | 0.6687 | 0.6634 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0