---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: correct_distilBERT_token_itr0_1e-05_essays_01_03_2022-15_41_29
  results: []
---

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# correct_distilBERT_token_itr0_1e-05_essays_01_03_2022-15_41_29

This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3097
- Precision: 0.2769
- Recall: 0.4391
- F1: 0.3396
- Accuracy: 0.8878

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 11   | 0.4573          | 0.0094    | 0.0027 | 0.0042 | 0.7702   |
| No log        | 2.0   | 22   | 0.3660          | 0.1706    | 0.3253 | 0.2239 | 0.8516   |
| No log        | 3.0   | 33   | 0.3096          | 0.2339    | 0.408  | 0.2974 | 0.8827   |
| No log        | 4.0   | 44   | 0.2868          | 0.2963    | 0.4693 | 0.3633 | 0.8928   |
| No log        | 5.0   | 55   | 0.2798          | 0.3141    | 0.48   | 0.3797 | 0.8960   |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3