---
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-large-uncased-hate-offensive-normal-speech-lr-1e-05
  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-large-uncased-hate-offensive-normal-speech-lr-1e-05

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0727
- Accuracy: 0.9772
- Weighted f1: 0.9772
- Weighted recall: 0.9772
- Weighted precision: 0.9773
- Micro f1: 0.9772
- Micro recall: 0.9772
- Micro precision: 0.9772
- Macro f1: 0.9756
- Macro recall: 0.9755
- Macro precision: 0.9757

## 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: 1e-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Weighted recall | Weighted precision | Micro f1 | Micro recall | Micro precision | Macro f1 | Macro recall | Macro precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:---------------:|:------------------:|:--------:|:------------:|:---------------:|:--------:|:------------:|:---------------:|
| 0.9139        | 1.0   | 153  | 0.4854          | 0.8111   | 0.8086      | 0.8111          | 0.8125             | 0.8111   | 0.8111       | 0.8111          | 0.7947   | 0.7932       | 0.8030          |
| 0.2278        | 2.0   | 306  | 0.0775          | 0.9674   | 0.9675      | 0.9674          | 0.9683             | 0.9674   | 0.9674       | 0.9674          | 0.9652   | 0.9657       | 0.9655          |
| 0.0582        | 3.0   | 459  | 0.1007          | 0.9772   | 0.9773      | 0.9772          | 0.9782             | 0.9772   | 0.9772       | 0.9772          | 0.9757   | 0.9754       | 0.9769          |
| 0.0228        | 4.0   | 612  | 0.0727          | 0.9772   | 0.9772      | 0.9772          | 0.9773             | 0.9772   | 0.9772       | 0.9772          | 0.9756   | 0.9755       | 0.9757          |
| 0.0159        | 5.0   | 765  | 0.1013          | 0.9739   | 0.9740      | 0.9739          | 0.9741             | 0.9739   | 0.9739       | 0.9739          | 0.9720   | 0.9719       | 0.9723          |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.6.dev0
- Tokenizers 0.13.3