---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: model_perturbations
  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. -->

# model_perturbations

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1463
- Precision: 0.4596
- Recall: 0.3968
- F1: 0.4259
- Accuracy: 0.9632

## 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
- 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   | 205  | 0.1769          | 0.2719    | 0.2810 | 0.2763 | 0.9532   |
| No log        | 2.0   | 410  | 0.1463          | 0.4596    | 0.3968 | 0.4259 | 0.9632   |
| 0.2289        | 3.0   | 615  | 0.1463          | 0.4382    | 0.4556 | 0.4467 | 0.9636   |
| 0.2289        | 4.0   | 820  | 0.1517          | 0.4951    | 0.4810 | 0.4879 | 0.9657   |
| 0.0817        | 5.0   | 1025 | 0.1540          | 0.5101    | 0.4825 | 0.4959 | 0.9663   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.0+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2