ana-grassmann
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End of training
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README.md
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---
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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: bert-base-uncased-finetuned-spam-real
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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-base-uncased-finetuned-spam-real
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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: 0.0342
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- Accuracy: 0.9942
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- F1: 0.9945
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- Precision: 0.9941
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- Recall: 0.9949
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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: 3.8529031222986405e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 15
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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: 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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| 0.0418 | 1.0 | 4173 | 0.0471 | 0.9877 | 0.9882 | 0.9950 | 0.9815 |
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| 0.0186 | 2.0 | 8346 | 0.0394 | 0.9935 | 0.9938 | 0.9938 | 0.9938 |
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| 0.0096 | 3.0 | 12519 | 0.0342 | 0.9942 | 0.9945 | 0.9941 | 0.9949 |
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| 0.0059 | 4.0 | 16692 | 0.0421 | 0.9934 | 0.9937 | 0.9958 | 0.9917 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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model.safetensors
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runs/Apr14_19-53-18_6ec9497f7a76/events.out.tfevents.1713131588.6ec9497f7a76.2144.7
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