|
--- |
|
license: apache-2.0 |
|
base_model: cross-encoder/ms-marco-MiniLM-L-6-v2 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
model-index: |
|
- name: ce-MiniLM-L6layer |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# ce-MiniLM-L6layer |
|
|
|
This model is a fine-tuned version of [cross-encoder/ms-marco-MiniLM-L-6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L-6-v2) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1559 |
|
- Accuracy: 0.7273 |
|
- Precision: 0.9091 |
|
- Recall: 0.6349 |
|
|
|
## 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-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:| |
|
| 12.9679 | 1.0 | 56 | 20.2827 | 0.6970 | 0.7797 | 0.7302 | |
|
| 9.2483 | 2.0 | 112 | 12.1491 | 0.6465 | 0.7188 | 0.7302 | |
|
| 1.9612 | 3.0 | 168 | 1.7406 | 0.6667 | 0.8409 | 0.5873 | |
|
| 0.5046 | 4.0 | 224 | 0.4060 | 0.6061 | 0.8158 | 0.4921 | |
|
| 0.3575 | 5.0 | 280 | 0.2410 | 0.6667 | 0.7885 | 0.6508 | |
|
| 0.244 | 6.0 | 336 | 0.1860 | 0.6263 | 0.9062 | 0.4603 | |
|
| 0.2324 | 7.0 | 392 | 0.1706 | 0.6970 | 0.9231 | 0.5714 | |
|
| 0.1958 | 8.0 | 448 | 0.1873 | 0.7172 | 0.7869 | 0.7619 | |
|
| 0.1687 | 9.0 | 504 | 0.1742 | 0.7778 | 0.8868 | 0.7460 | |
|
| 0.1581 | 10.0 | 560 | 0.1559 | 0.7273 | 0.9091 | 0.6349 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.2.1 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.15.1 |
|
|
