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  1. README.md +71 -0
  2. model.safetensors +1 -1
README.md ADDED
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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: NLPGroupProject-Finetune-DistilBert
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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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+ # NLPGroupProject-Finetune-DistilBert
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+
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+ This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/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: 1.1391
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+ - Accuracy: 0.723
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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: 5e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.25 | 250 | 0.9720 | 0.69 |
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+ | 0.9562 | 0.5 | 500 | 0.8417 | 0.707 |
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+ | 0.9562 | 0.75 | 750 | 0.7335 | 0.73 |
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+ | 0.8908 | 1.0 | 1000 | 0.7306 | 0.739 |
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+ | 0.8908 | 1.25 | 1250 | 0.7490 | 0.721 |
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+ | 0.646 | 1.5 | 1500 | 0.7560 | 0.738 |
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+ | 0.646 | 1.75 | 1750 | 0.7759 | 0.73 |
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+ | 0.6244 | 2.0 | 2000 | 0.8180 | 0.723 |
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+ | 0.6244 | 2.25 | 2250 | 1.0023 | 0.722 |
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+ | 0.359 | 2.5 | 2500 | 1.0590 | 0.728 |
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+ | 0.359 | 2.75 | 2750 | 1.0733 | 0.723 |
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+ | 0.3716 | 3.0 | 3000 | 1.1391 | 0.723 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.2+cu118
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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