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---
license: apache-2.0
base_model: distilbert/distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-cased-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-cased-clickbait-task1-20-epoch-post_title
This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4958
- Accuracy: 0.6475
## 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 | 0.8537 | 0.6225 |
| No log | 2.0 | 400 | 0.8157 | 0.65 |
| 0.8073 | 3.0 | 600 | 0.8731 | 0.6525 |
| 0.8073 | 4.0 | 800 | 0.9890 | 0.6825 |
| 0.3328 | 5.0 | 1000 | 1.2191 | 0.6325 |
| 0.3328 | 6.0 | 1200 | 1.4974 | 0.675 |
| 0.3328 | 7.0 | 1400 | 1.7291 | 0.6575 |
| 0.0842 | 8.0 | 1600 | 1.9302 | 0.65 |
| 0.0842 | 9.0 | 1800 | 2.0243 | 0.66 |
| 0.0262 | 10.0 | 2000 | 2.1548 | 0.6525 |
| 0.0262 | 11.0 | 2200 | 2.3360 | 0.64 |
| 0.0262 | 12.0 | 2400 | 2.2967 | 0.655 |
| 0.0088 | 13.0 | 2600 | 2.2970 | 0.6525 |
| 0.0088 | 14.0 | 2800 | 2.3359 | 0.6425 |
| 0.0058 | 15.0 | 3000 | 2.4252 | 0.6525 |
| 0.0058 | 16.0 | 3200 | 2.4796 | 0.6575 |
| 0.0058 | 17.0 | 3400 | 2.4698 | 0.645 |
| 0.0033 | 18.0 | 3600 | 2.4963 | 0.645 |
| 0.0033 | 19.0 | 3800 | 2.4821 | 0.6475 |
| 0.0022 | 20.0 | 4000 | 2.4958 | 0.6475 |
### Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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