---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: BERT_model_new
  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. -->

# BERT_model_new

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1206
- F1: 0.8301

## Model description

train_df = pd.read_csv('/content/drive/My Drive/DATASETS/wiki_toxic/train.csv')\
validation_df = pd.read_csv('/content/drive/My Drive/DATASETS/wiki_toxic/validation.csv')\
#test_df = pd.read_csv('/content/drive/My Drive/wiki_toxic/test.csv')\
frac = 0.9\
#TRAIN\
print(train_df.shape[0]) # get the number of rows in the dataframe\
rows_to_delete = train_df.sample(frac=frac, random_state=1)\
train_df = train_df.drop(rows_to_delete.index)\
print(train_df.shape[0])\

#VALIDATION\
print(validation_df.shape[0]) # get the number of rows in the dataframe\
rows_to_delete = validation_df.sample(frac=frac, random_state=1)\
validation_df = validation_df.drop(rows_to_delete.index)\
print(validation_df.shape[0])\

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 399  | 0.0940          | 0.8273 |
| 0.1262        | 2.0   | 798  | 0.1206          | 0.8301 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3