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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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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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- precision |
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- recall |
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model-index: |
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- name: results |
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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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# results |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on Reddit social media dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2235 |
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- Accuracy: 0.9579 |
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- F1: 0.9579 |
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- Precision: 0.9580 |
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- Recall: 0.9579 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 10 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.1672 | 1.0 | 543 | 0.2845 | 0.9280 | 0.9279 | 0.9329 | 0.9285 | |
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| 0.2139 | 2.0 | 1086 | 0.2221 | 0.9439 | 0.9439 | 0.9447 | 0.9441 | |
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| 0.1531 | 3.0 | 1629 | 0.2010 | 0.9523 | 0.9523 | 0.9526 | 0.9522 | |
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| 0.0002 | 4.0 | 2172 | 0.2235 | 0.9579 | 0.9579 | 0.9580 | 0.9579 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.5.0+cu121 |
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- Tokenizers 0.19.1 |
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