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annavines/roberta_2ep_2e5lr

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: roberta-base
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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: finetune_output
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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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+ # finetune_output
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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 None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1540
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+ - Precision: 0.9636
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+ - Recall: 0.9510
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+ - F1: 0.9573
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+ - Accuracy: 0.952
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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: 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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+ - num_epochs: 2
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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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+ | 0.3726 | 0.75 | 100 | 0.1531 | 0.9551 | 0.9467 | 0.9509 | 0.946 |
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+ | 0.1662 | 1.49 | 200 | 0.1540 | 0.9636 | 0.9510 | 0.9573 | 0.952 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.1
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.2
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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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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "LABEL_0",
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+ },
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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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+ "torch_dtype": "float32",
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+ "transformers_version": "4.32.1",
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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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