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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-uncased-finetuned-zindi_tweets
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. -->
# distilbert-base-uncased-finetuned-zindi_tweets
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: 0.3203
- Accuracy: 0.9168
- F1: 0.9168
## 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: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4224 | 1.0 | 67 | 0.2924 | 0.8894 | 0.8893 |
| 0.2096 | 2.0 | 134 | 0.2632 | 0.9055 | 0.9055 |
| 0.1329 | 3.0 | 201 | 0.2744 | 0.9102 | 0.9101 |
| 0.1016 | 4.0 | 268 | 0.2868 | 0.9055 | 0.9054 |
| 0.0752 | 5.0 | 335 | 0.2896 | 0.9140 | 0.9140 |
| 0.0454 | 6.0 | 402 | 0.3077 | 0.9178 | 0.9178 |
| 0.0305 | 7.0 | 469 | 0.3185 | 0.9149 | 0.9149 |
| 0.0298 | 8.0 | 536 | 0.3203 | 0.9168 | 0.9168 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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