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README.md CHANGED
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  ---
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  license: apache-2.0
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+ - f1
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+ model-index:
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+ - name: pharma_classification
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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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+ # pharma_classification
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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: 0.5315
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+ - Accuracy: 0.9581
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+ - F1: 0.9506
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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: 8
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+ - eval_batch_size: 8
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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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+ - training_steps: 30000
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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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+ | 0.0035 | 5.99 | 5000 | 0.2892 | 0.9539 | 0.9554 |
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+ | 0.0137 | 11.98 | 10000 | 0.2620 | 0.9641 | 0.9600 |
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+ | 0.0 | 17.96 | 15000 | 0.4022 | 0.9611 | 0.9586 |
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+ | 0.0001 | 23.95 | 20000 | 0.3838 | 0.9611 | 0.9552 |
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+ | 0.0 | 29.94 | 25000 | 0.4363 | 0.9575 | 0.9490 |
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+ | 0.0 | 35.93 | 30000 | 0.5315 | 0.9581 | 0.9506 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.0.dev0
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+ - Pytorch 2.2.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
config.json ADDED
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+ "_name_or_path": "distilbert-base-uncased",
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+ "activation": "gelu",
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+ "DistilBertForSequenceClassification"
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+ ],
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+ "attention_dropout": 0.1,
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+ "initializer_range": 0.02,
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+ "model_type": "distilbert",
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+ "n_heads": 12,
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+ "n_layers": 6,
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+ "pad_token_id": 0,
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+ "problem_type": "single_label_classification",
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+ "qa_dropout": 0.1,
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+ "seq_classif_dropout": 0.2,
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+ "tie_weights_": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.39.0.dev0",
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+ "vocab_size": 30522
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+ }
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