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Training in progress, epoch 2

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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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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: insuff_supported_arguments
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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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+ # insuff_supported_arguments
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0000
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+ - Negative: {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 13620.0}
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+ - Positive: {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 6960.0}
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+ - Accuracy: 1.0
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+ - Macro avg: {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 20580.0}
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+ - Weighted avg: {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 20580.0}
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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: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Negative | Positive | Accuracy | Macro avg | Weighted avg |
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+ |:-------------:|:-----:|:----:|:---------------:|:----------------------------------------------------------------------:|:---------------------------------------------------------------------:|:--------:|:----------------------------------------------------------------------:|:----------------------------------------------------------------------:|
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+ | 0.0 | 1.0 | 4628 | 0.0000 | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 13620.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 6960.0} | 1.0 | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 20580.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 20580.0} |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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+ {
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+ "_name_or_path": "distilbert-base-uncased",
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+ "activation": "gelu",
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+ "architectures": [
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+ "DistilBertForSequenceClassification"
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+ ],
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+ "attention_dropout": 0.1,
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+ "dropout": 0.1,
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+ "hidden_dim": 3072,
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+ "id2label": {
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+ "1": "POSITIVE"
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+ },
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+ "n_layers": 6,
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+ "problem_type": "single_label_classification",
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+ "qa_dropout": 0.1,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.38.2",
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+ "vocab_size": 30522
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+ }
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