metadata
library_name: transformers
license: mit
base_model: BAAI/bge-small-en-v1.5
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: dl2_hw2
results: []
dl2_hw2
This model is a fine-tuned version of BAAI/bge-small-en-v1.5 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0818
- Precision: 0.8836
- Recall: 0.9139
- F1: 0.8985
- Accuracy: 0.9802
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0739 | 1.0 | 626 | 0.0923 | 0.8679 | 0.9072 | 0.8871 | 0.9780 |
| 0.064 | 2.0 | 1252 | 0.0834 | 0.8774 | 0.9145 | 0.8956 | 0.9795 |
| 0.0563 | 3.0 | 1878 | 0.0818 | 0.8836 | 0.9139 | 0.8985 | 0.9802 |
Framework versions
- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 4.1.1
- Tokenizers 0.21.2