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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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- precision
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- recall
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- f1
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model-index:
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- name: imdb-distilbert-sentiment
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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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# imdb-distilbert-sentiment
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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: 0.4325
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- Accuracy: 0.8796
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- Precision: 0.8725
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- Recall: 0.8892
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- F1: 0.8808
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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: 32
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- seed: 42
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- optimizer: Use 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: 3
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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 | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.3175 | 1.0 | 1563 | 0.3278 | 0.8607 | 0.9120 | 0.7985 | 0.8515 |
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| 0.2139 | 2.0 | 3126 | 0.3392 | 0.8773 | 0.8679 | 0.8901 | 0.8788 |
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| 0.1325 | 3.0 | 4689 | 0.4325 | 0.8796 | 0.8725 | 0.8892 | 0.8808 |
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### Framework versions
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- Transformers 4.57.0
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- Pytorch 2.5.1+cu121
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- Datasets 4.1.1
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- Tokenizers 0.22.1
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