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---
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
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