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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/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-finetuned-multiclass-classification
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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-finetuned-multiclass-classification
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6039
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- Accuracy: 0.9045
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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: 1.45e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 29
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- distributed_type: multi-GPU
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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: 5
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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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| 2.6788 | 1.0 | 2638 | 2.1418 | 0.7233 |
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| 1.289 | 2.0 | 5276 | 1.0718 | 0.8385 |
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| 0.7581 | 3.0 | 7914 | 0.7530 | 0.8878 |
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| 0.5557 | 4.0 | 10552 | 0.6371 | 0.9007 |
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| 0.493 | 5.0 | 13190 | 0.6039 | 0.9045 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 1.13.1+cpu
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- Datasets 2.13.1
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- Tokenizers 0.19.1
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