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---
library_name: keras
language:
- en
pipeline_tag: text-classification
tags:
- toxic
- comment
- toxic comment
---
## Model description
This model used for text classification with toxic and non-toxic labels.
## Intended uses & limitations
If you want to reuse model, try copy this
```
from huggingface_hub import from_pretrained_keras
reloaded_model = from_pretrained_keras('Johnesss/Toxic-Comment-Classification')
y_testing=reloaded_model.predict(x_testing,verbose=1,batch_size=32)
test_df['Toxic']=['Not Toxic' if x<0.5 else 'Toxic' for x in y_testing]
test_df[['comment_text','Toxic']].head(20)
```
## Training and evaluation data
Full info in .ipynb file
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
| Hyperparameters | Value |
| :-- | :-- |
| name | Adam |
| weight_decay | None |
| clipnorm | None |
| global_clipnorm | None |
| clipvalue | None |
| use_ema | False |
| ema_momentum | 0.99 |
| ema_overwrite_frequency | None |
| jit_compile | False |
| is_legacy_optimizer | False |
| learning_rate | 0.0010000000474974513 |
| beta_1 | 0.9 |
| beta_2 | 0.999 |
| epsilon | 1e-07 |
| amsgrad | False |
| training_precision | float32 |
## Model Plot
<details>
<summary>View Model Plot</summary>
</details> |