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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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model-index:
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- name: distilbert-base-uncased-finetuned-zindi_tweets
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# distilbert-base-uncased-finetuned-zindi_tweets
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3203
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- Accuracy: 0.9168
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- F1: 0.9168
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 8
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.4224 | 1.0 | 67 | 0.2924 | 0.8894 | 0.8893 |
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| 0.2096 | 2.0 | 134 | 0.2632 | 0.9055 | 0.9055 |
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| 0.1329 | 3.0 | 201 | 0.2744 | 0.9102 | 0.9101 |
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| 0.1016 | 4.0 | 268 | 0.2868 | 0.9055 | 0.9054 |
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| 0.0752 | 5.0 | 335 | 0.2896 | 0.9140 | 0.9140 |
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| 0.0454 | 6.0 | 402 | 0.3077 | 0.9178 | 0.9178 |
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| 0.0305 | 7.0 | 469 | 0.3185 | 0.9149 | 0.9149 |
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| 0.0298 | 8.0 | 536 | 0.3203 | 0.9168 | 0.9168 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.11.0+cu113
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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