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update model card README.md

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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: distilbert-base-uncased-finetuned-dwnews-categories
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+ results: []
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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-dwnews-categories
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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 None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8331
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+ - F1: 0.7310
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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: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 2.0432 | 0.3 | 30 | 1.8112 | 0.2093 |
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+ | 1.7228 | 0.6 | 60 | 1.4949 | 0.3650 |
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+ | 1.3799 | 0.9 | 90 | 1.2691 | 0.5838 |
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+ | 1.2261 | 1.2 | 120 | 1.1287 | 0.6345 |
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+ | 1.0695 | 1.5 | 150 | 1.0383 | 0.6723 |
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+ | 0.9634 | 1.8 | 180 | 0.9570 | 0.7279 |
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+ | 0.9289 | 2.1 | 210 | 0.9106 | 0.7435 |
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+ | 0.8258 | 2.4 | 240 | 0.9380 | 0.7130 |
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+ | 0.7692 | 2.7 | 270 | 0.8708 | 0.7262 |
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+ | 0.7542 | 3.0 | 300 | 0.8568 | 0.7350 |
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+ | 0.6584 | 3.3 | 330 | 0.8447 | 0.7368 |
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+ | 0.5871 | 3.6 | 360 | 0.8517 | 0.7226 |
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+ | 0.6528 | 3.9 | 390 | 0.8471 | 0.7290 |
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+ | 0.5805 | 4.2 | 420 | 0.8085 | 0.7291 |
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+ | 0.5904 | 4.5 | 450 | 0.8331 | 0.7310 |
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+ | 0.4877 | 4.8 | 480 | 0.8334 | 0.7209 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Pytorch 1.13.1+cu116
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+ - Datasets 2.10.0
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+ - Tokenizers 0.13.2