logichacker
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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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datasets:
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- swag
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metrics:
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- accuracy
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model-index:
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- name: my_awesome_swag_model
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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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# my_awesome_swag_model
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the swag dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0449
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- Accuracy: 0.7878
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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: 16
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- eval_batch_size: 16
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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: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 0.7784 | 1.0 | 4597 | 0.5916 | 0.7655 |
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| 0.3817 | 2.0 | 9194 | 0.6262 | 0.7813 |
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| 0.1508 | 3.0 | 13791 | 1.0449 | 0.7878 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu118
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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model.safetensors
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