|
--- |
|
license: mit |
|
base_model: thenlper/gte-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: gte-base-clickbait-task1-post |
|
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. --> |
|
|
|
# gte-base-clickbait-task1-post |
|
|
|
This model is a fine-tuned version of [thenlper/gte-base](https://huggingface.co/thenlper/gte-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.4369 |
|
- Accuracy: 0.69 |
|
|
|
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 1.0 | 200 | 0.8074 | 0.6575 | |
|
| No log | 2.0 | 400 | 0.7113 | 0.7225 | |
|
| 0.7726 | 3.0 | 600 | 0.7627 | 0.7375 | |
|
| 0.7726 | 4.0 | 800 | 0.9634 | 0.72 | |
|
| 0.268 | 5.0 | 1000 | 1.2732 | 0.6925 | |
|
| 0.268 | 6.0 | 1200 | 1.5238 | 0.715 | |
|
| 0.268 | 7.0 | 1400 | 1.8239 | 0.6875 | |
|
| 0.0465 | 8.0 | 1600 | 1.9875 | 0.7 | |
|
| 0.0465 | 9.0 | 1800 | 2.1233 | 0.68 | |
|
| 0.0147 | 10.0 | 2000 | 2.1624 | 0.6775 | |
|
| 0.0147 | 11.0 | 2200 | 2.3234 | 0.6725 | |
|
| 0.0147 | 12.0 | 2400 | 2.2247 | 0.6975 | |
|
| 0.0087 | 13.0 | 2600 | 2.3189 | 0.685 | |
|
| 0.0087 | 14.0 | 2800 | 2.3079 | 0.69 | |
|
| 0.0055 | 15.0 | 3000 | 2.4370 | 0.6825 | |
|
| 0.0055 | 16.0 | 3200 | 2.4838 | 0.6775 | |
|
| 0.0055 | 17.0 | 3400 | 2.4335 | 0.6775 | |
|
| 0.0047 | 18.0 | 3600 | 2.4259 | 0.6775 | |
|
| 0.0047 | 19.0 | 3800 | 2.4417 | 0.6825 | |
|
| 0.0043 | 20.0 | 4000 | 2.4369 | 0.69 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0.dev0 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|