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End of training

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README.md ADDED
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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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+ datasets:
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+ - imdb
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+ metrics:
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+ - accuracy
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+ - f1
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+ model-index:
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+ - name: distilbert-base-uncased-finetuned-imdb
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: imdb
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+ type: imdb
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+ config: plain_text
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+ split: test
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+ args: plain_text
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value:
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+ accuracy: 0.93192
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+ - name: F1
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+ type: f1
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+ value:
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+ f1: 0.9319183250818663
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+ ---
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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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+
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+ # distilbert-base-uncased-finetuned-imdb
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2776
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+ - Accuracy: {'accuracy': 0.93192}
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+ - F1: {'f1': 0.9319183250818663}
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+ - 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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------------------:|:--------------------------:|
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+ | 0.227 | 1.0 | 1563 | 0.2893 | {'accuracy': 0.89856} | {'f1': 0.8979731717204342} |
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+ | 0.16 | 2.0 | 3126 | 0.2327 | {'accuracy': 0.92876} | {'f1': 0.9287230772995674} |
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+ | 0.0914 | 3.0 | 4689 | 0.2776 | {'accuracy': 0.93192} | {'f1': 0.9319183250818663} |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.1
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
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