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README.md
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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: 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: distilbert-base-uncased-distilled-clinc
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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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# distilbert-base-uncased-distilled-clinc
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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: 0.7144
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- Accuracy: 0.9458
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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: 48
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- eval_batch_size: 48
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 10
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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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| 6.0788 | 1.0 | 318 | 4.2118 | 0.7068 |
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| 3.1783 | 2.0 | 636 | 1.9113 | 0.8548 |
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| 1.5075 | 3.0 | 954 | 1.0655 | 0.9087 |
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| 0.8843 | 4.0 | 1272 | 0.8456 | 0.9332 |
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| 0.6849 | 5.0 | 1590 | 0.7832 | 0.9381 |
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| 0.606 | 6.0 | 1908 | 0.7561 | 0.9426 |
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| 0.5681 | 7.0 | 2226 | 0.7347 | 0.9452 |
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| 0.5453 | 8.0 | 2544 | 0.7227 | 0.9439 |
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| 0.5339 | 9.0 | 2862 | 0.7156 | 0.9452 |
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| 0.527 | 10.0 | 3180 | 0.7144 | 0.9458 |
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### Framework versions
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- Transformers 4.46.0
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- Pytorch 2.5.0
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- Datasets 3.0.2
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- Tokenizers 0.20.1
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