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.gitignore ADDED
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+ checkpoint-*/
README.md ADDED
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+ ---
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+ license: mit
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - conll2003
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+ model_index:
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+ - name: roberta-base-ner
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: conll2003
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+ type: conll2003
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+ args: conll2003
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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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+ # roberta-base-ner
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the conll2003 dataset.
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+ It achieves the following results on the evaluation set:
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+ - eval_loss: 0.0814
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+ - eval_precision: 0.9101
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+ - eval_recall: 0.9336
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+ - eval_f1: 0.9217
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+ - eval_accuracy: 0.9799
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+ - eval_runtime: 10.2964
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+ - eval_samples_per_second: 315.646
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+ - eval_steps_per_second: 39.529
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+ - epoch: 1.14
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+ - step: 500
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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: 32
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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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+ - num_epochs: 4.0
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+
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+ ### Framework versions
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+
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+ - Transformers 4.8.2
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+ - Pytorch 1.8.1+cu111
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+ - Datasets 1.8.0
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+ - Tokenizers 0.10.3
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+ {
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+ "_name_or_path": "roberta-base",
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+ "architectures": [
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+ "RobertaForTokenClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "bos_token_id": 0,
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+ "eos_token_id": 2,
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 514,
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "transformers_version": "4.8.2",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ "vocab_size": 50265
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+ }
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