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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: distilbert-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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model-index:
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- name: checkpoints
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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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# checkpoints
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8798
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- Accuracy: 0.8667
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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: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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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: 10
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- mixed_precision_training: Native AMP
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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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| 1.0973 | 1.0 | 2 | 1.0807 | 0.4667 |
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| 1.0801 | 2.0 | 4 | 1.0622 | 0.5333 |
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| 1.0713 | 3.0 | 6 | 1.0386 | 0.5333 |
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| 1.0396 | 4.0 | 8 | 1.0092 | 0.6 |
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| 1.0034 | 5.0 | 10 | 0.9786 | 0.8 |
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| 0.9929 | 6.0 | 12 | 0.9501 | 0.8667 |
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| 0.9552 | 7.0 | 14 | 0.9236 | 0.8667 |
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| 0.9386 | 8.0 | 16 | 0.9011 | 0.8667 |
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| 0.9084 | 9.0 | 18 | 0.8862 | 0.8667 |
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| 0.897 | 10.0 | 20 | 0.8798 | 0.8667 |
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### Framework versions
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- Transformers 4.41.0
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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