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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: bert-tweet-disaster
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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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# bert-tweet-disaster
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9563
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- Accuracy: 0.8320
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- F1: 0.8095
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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: 5e-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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- lr_scheduler_warmup_steps: 500
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- num_epochs: 10
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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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| 0.605 | 1.0 | 108 | 0.4455 | 0.8123 | 0.7741 |
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| 0.3878 | 2.0 | 216 | 0.3940 | 0.8438 | 0.8126 |
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| 0.3228 | 3.0 | 324 | 0.4441 | 0.8241 | 0.8006 |
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| 0.2526 | 4.0 | 432 | 0.4714 | 0.8333 | 0.8006 |
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| 0.2002 | 5.0 | 540 | 0.5677 | 0.8189 | 0.7890 |
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| 0.1391 | 6.0 | 648 | 0.6633 | 0.8307 | 0.8000 |
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| 0.0922 | 7.0 | 756 | 0.8019 | 0.8294 | 0.8071 |
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| 0.0693 | 8.0 | 864 | 0.8526 | 0.8333 | 0.8049 |
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| 0.0495 | 9.0 | 972 | 0.9813 | 0.8241 | 0.8075 |
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| 0.0345 | 10.0 | 1080 | 0.9563 | 0.8320 | 0.8095 |
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### Framework versions
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- Transformers 4.20.1
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- Pytorch 1.11.0
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- Datasets 2.1.0
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- Tokenizers 0.12.1
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