transformers pytorch tensorboard bert text-classification generated_from_trainer dataset:eoir_privacy license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- eoir_privacy
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: bert_uncased_L-4_H-512_A-8-finetuned-eoir_privacy-longer
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: eoir_privacy
      type: eoir_privacy
      config: all
      split: train
      args: all
    metrics:
    - type: accuracy
      value: 0.9476327116212339
      name: Accuracy
    - type: f1
      value: 0.8805237315875615
      name: F1
---

<!-- 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_uncased_L-4_H-512_A-8-finetuned-eoir_privacy-longer

This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the eoir_privacy dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1738
- Accuracy: 0.9476
- F1: 0.8805

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 63   | 0.2004          | 0.9261   | 0.8298 |
| No log        | 2.0   | 126  | 0.2042          | 0.9297   | 0.8435 |
| No log        | 3.0   | 189  | 0.1888          | 0.9362   | 0.8558 |
| No log        | 4.0   | 252  | 0.1879          | 0.9383   | 0.8532 |
| No log        | 5.0   | 315  | 0.1715          | 0.9462   | 0.8788 |
| No log        | 6.0   | 378  | 0.1761          | 0.9448   | 0.8706 |
| No log        | 7.0   | 441  | 0.1730          | 0.9455   | 0.8774 |
| 0.1078        | 8.0   | 504  | 0.1753          | 0.9448   | 0.8772 |
| 0.1078        | 9.0   | 567  | 0.1721          | 0.9469   | 0.8791 |
| 0.1078        | 10.0  | 630  | 0.1738          | 0.9476   | 0.8805 |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
