transformers pytorch tensorboard safetensors bert text-classification generated_from_trainer dataset:eoir_privacy model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- eoir_privacy
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: bert_uncased_L-4_H-512_A-8-finetuned-eoir_privacy-longer-finetuned-eoir_privacy-longer20
  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: 0.9469153515064562
      name: Accuracy
    - type: f1
      value: 0.8782894736842105
      name: F1
---

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# bert_uncased_L-4_H-512_A-8-finetuned-eoir_privacy-longer-finetuned-eoir_privacy-longer20

This model was trained from scratch on the eoir_privacy dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1994
- Accuracy: 0.9469
- F1: 0.8783

## 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   | 0.2134          | 0.9412   | 0.8581 |
| No log        | 2.0   | 126  | 0.2083          | 0.9405   | 0.8610 |
| No log        | 3.0   | 189  | 0.2108          | 0.9448   | 0.8702 |
| No log        | 4.0   | 252  | 0.2281          | 0.9397   | 0.8537 |
| No log        | 5.0   | 315  | 0.2034          | 0.9469   | 0.8783 |
| No log        | 6.0   | 378  | 0.2133          | 0.9419   | 0.8629 |
| No log        | 7.0   | 441  | 0.1971          | 0.9440   | 0.8746 |
| 0.0525        | 8.0   | 504  | 0.2013          | 0.9455   | 0.8778 |
| 0.0525        | 9.0   | 567  | 0.1987          | 0.9469   | 0.8787 |
| 0.0525        | 10.0  | 630  | 0.1994          | 0.9469   | 0.8783 |


### Framework versions

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