---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-zindi_tweets2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-finetuned-zindi_tweets2

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3185
- Accuracy: 0.9216
- F1: 0.9216

## 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: 64
- eval_batch_size: 64
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.0938        | 1.0   | 67   | 0.2077          | 0.9301   | 0.9301 |
| 0.0429        | 2.0   | 134  | 0.2581          | 0.9244   | 0.9244 |
| 0.028         | 3.0   | 201  | 0.3246          | 0.9159   | 0.9157 |
| 0.0177        | 4.0   | 268  | 0.3317          | 0.9206   | 0.9205 |
| 0.0128        | 5.0   | 335  | 0.3185          | 0.9216   | 0.9216 |


### Framework versions

- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1