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---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-clickbait-task1-20-epoch-post_title
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. -->
# distilbert-base-uncased-clickbait-task1-20-epoch-post_title
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co./distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4236
- Accuracy: 0.67
## 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 | 0.8500 | 0.6425 |
| No log | 2.0 | 400 | 0.7542 | 0.6975 |
| 0.7863 | 3.0 | 600 | 0.8059 | 0.695 |
| 0.7863 | 4.0 | 800 | 0.9656 | 0.6875 |
| 0.3245 | 5.0 | 1000 | 1.1785 | 0.655 |
| 0.3245 | 6.0 | 1200 | 1.4214 | 0.675 |
| 0.3245 | 7.0 | 1400 | 1.7879 | 0.655 |
| 0.0784 | 8.0 | 1600 | 1.9526 | 0.66 |
| 0.0784 | 9.0 | 1800 | 2.0289 | 0.6575 |
| 0.0233 | 10.0 | 2000 | 2.1091 | 0.675 |
| 0.0233 | 11.0 | 2200 | 2.1530 | 0.67 |
| 0.0233 | 12.0 | 2400 | 2.2120 | 0.67 |
| 0.0091 | 13.0 | 2600 | 2.2703 | 0.6875 |
| 0.0091 | 14.0 | 2800 | 2.3026 | 0.68 |
| 0.0064 | 15.0 | 3000 | 2.3154 | 0.685 |
| 0.0064 | 16.0 | 3200 | 2.3335 | 0.6825 |
| 0.0064 | 17.0 | 3400 | 2.3667 | 0.6825 |
| 0.0036 | 18.0 | 3600 | 2.3959 | 0.6775 |
| 0.0036 | 19.0 | 3800 | 2.4513 | 0.6625 |
| 0.0043 | 20.0 | 4000 | 2.4236 | 0.67 |
### Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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