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distilbert-classn-LAlg-multihead-context-width-4

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Classification Training

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  1. README.md +86 -0
  2. model.safetensors +1 -1
  3. runs/Feb20_17-28-17_5620a5a217a0/events.out.tfevents.1740072499.5620a5a217a0.1082.8 +2 -2
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: dslim/distilbert-NER
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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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+ - precision
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+ - recall
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+ model-index:
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+ - name: distilbert-classn-LAlg-multihead-context-width-4
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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-classn-LAlg-multihead-context-width-4
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+
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+ This model is a fine-tuned version of [dslim/distilbert-NER](https://huggingface.co/dslim/distilbert-NER) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9001
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+ - Accuracy: 0.7778
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+ - F1: 0.7818
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+ - Precision: 0.8035
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+ - Recall: 0.7778
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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: 1e-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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 25
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+ - mixed_precision_training: Native AMP
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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 | Precision | Recall |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 2.4495 | 1.3514 | 50 | 2.5136 | 0.0556 | 0.0522 | 0.1279 | 0.0556 |
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+ | 2.4414 | 2.7027 | 100 | 2.5005 | 0.0714 | 0.0678 | 0.0799 | 0.0714 |
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+ | 2.4231 | 4.0541 | 150 | 2.4821 | 0.0714 | 0.0718 | 0.0911 | 0.0714 |
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+ | 2.3702 | 5.4054 | 200 | 2.4614 | 0.0873 | 0.0946 | 0.1167 | 0.0873 |
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+ | 2.3442 | 6.7568 | 250 | 2.4363 | 0.0714 | 0.0651 | 0.0683 | 0.0714 |
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+ | 2.271 | 8.1081 | 300 | 2.3787 | 0.1349 | 0.1268 | 0.1264 | 0.1349 |
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+ | 2.1474 | 9.4595 | 350 | 2.2815 | 0.1746 | 0.1619 | 0.1687 | 0.1746 |
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+ | 1.9343 | 10.8108 | 400 | 2.0912 | 0.3413 | 0.3320 | 0.3770 | 0.3413 |
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+ | 1.6174 | 12.1622 | 450 | 1.8072 | 0.4524 | 0.4455 | 0.5545 | 0.4524 |
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+ | 1.1783 | 13.5135 | 500 | 1.4265 | 0.6111 | 0.6193 | 0.6449 | 0.6111 |
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+ | 0.7923 | 14.8649 | 550 | 1.1770 | 0.6905 | 0.6985 | 0.7139 | 0.6905 |
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+ | 0.4365 | 16.2162 | 600 | 1.0497 | 0.7143 | 0.7147 | 0.7417 | 0.7143 |
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+ | 0.2509 | 17.5676 | 650 | 0.9858 | 0.7460 | 0.7486 | 0.7734 | 0.7460 |
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+ | 0.1531 | 18.9189 | 700 | 0.9514 | 0.7460 | 0.7506 | 0.7804 | 0.7460 |
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+ | 0.0923 | 20.2703 | 750 | 0.9163 | 0.7698 | 0.7709 | 0.7911 | 0.7698 |
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+ | 0.0653 | 21.6216 | 800 | 0.9064 | 0.7778 | 0.7797 | 0.7978 | 0.7778 |
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+ | 0.0509 | 22.9730 | 850 | 0.9130 | 0.7778 | 0.7801 | 0.8004 | 0.7778 |
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+ | 0.04 | 24.3243 | 900 | 0.9001 | 0.7778 | 0.7818 | 0.8035 | 0.7778 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.3
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.3.1
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+ - Tokenizers 0.21.0
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