m-aliabbas1 commited on
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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: prajjwal1/bert-tiny
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: mva_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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+ # mva_ner
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+
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+ This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0001
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+ - Overall Precision: 1.0
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+ - Overall Recall: 1.0
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+ - Overall F1: 1.0
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+ - Overall Accuracy: 1.0
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+ - Year F1: 1.0
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+ - Years Ago F1: 1.0
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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: 0.0002
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+ - train_batch_size: 16
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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: 150
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Year F1 | Years Ago F1 |
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+ |:-------------:|:------:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:-------:|:------------:|
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+ | 0.0171 | 55.56 | 1000 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.0005 | 111.11 | 2000 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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+ "_name_or_path": "prajjwal1/bert-tiny",
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+ ],
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "bert",
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+ "num_attention_heads": 2,
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+ "num_hidden_layers": 2,
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+ "position_embedding_type": "absolute",
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+ "torch_dtype": "float32",
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