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---
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
|