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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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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: distilbert-base-uncased-finetuned-custom-ner
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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-custom-ner
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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: 0.7017
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+ - Precision: 0.2292
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+ - Recall: 0.275
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+ - F1: 0.25
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+ - Accuracy: 0.8598
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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 | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 1 | 0.8583 | 0.1045 | 0.175 | 0.1308 | 0.8084 |
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+ | No log | 2.0 | 2 | 0.7963 | 0.1228 | 0.175 | 0.1443 | 0.8271 |
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+ | No log | 3.0 | 3 | 0.7497 | 0.1837 | 0.225 | 0.2022 | 0.8505 |
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+ | No log | 4.0 | 4 | 0.7179 | 0.1837 | 0.225 | 0.2022 | 0.8505 |
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+ | No log | 5.0 | 5 | 0.7017 | 0.2292 | 0.275 | 0.25 | 0.8598 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.14.1
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+ - Tokenizers 0.19.1
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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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+ "DistilBertForTokenClassification"
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+ ],
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+ "attention_dropout": 0.1,
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+ "max_position_embeddings": 512,
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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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+ "tie_weights_": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.41.2",
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+ "vocab_size": 30522
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+ }
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