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distilbert-classn-LinearAlg-finetuned-pred-span-width-3

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Classification Training

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  2. runs/Feb20_15-27-28_ed60d19afb74/events.out.tfevents.1740065251.ed60d19afb74.10154.0 +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-LinearAlg-finetuned-pred-span-width-3
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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-LinearAlg-finetuned-pred-span-width-3
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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: 0.7560
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+ - Accuracy: 0.8175
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+ - F1: 0.8136
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+ - Precision: 0.8277
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+ - Recall: 0.8175
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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: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 4
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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: 20
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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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+ | 4.9235 | 0.6849 | 50 | 2.4998 | 0.0556 | 0.0219 | 0.0142 | 0.0556 |
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+ | 4.8853 | 1.3699 | 100 | 2.4692 | 0.0556 | 0.0227 | 0.0148 | 0.0556 |
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+ | 4.8296 | 2.0548 | 150 | 2.4199 | 0.0794 | 0.0499 | 0.0414 | 0.0794 |
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+ | 4.7138 | 2.7397 | 200 | 2.3605 | 0.1111 | 0.0778 | 0.0800 | 0.1111 |
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+ | 4.5483 | 3.4247 | 250 | 2.2678 | 0.2222 | 0.2171 | 0.2713 | 0.2222 |
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+ | 4.4398 | 4.1096 | 300 | 2.1006 | 0.3730 | 0.3441 | 0.3723 | 0.3730 |
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+ | 4.031 | 4.7945 | 350 | 1.9045 | 0.5238 | 0.4995 | 0.5172 | 0.5238 |
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+ | 3.5384 | 5.4795 | 400 | 1.6756 | 0.6508 | 0.6382 | 0.6649 | 0.6508 |
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+ | 2.9989 | 6.1644 | 450 | 1.4537 | 0.7302 | 0.7116 | 0.7624 | 0.7302 |
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+ | 2.5192 | 6.8493 | 500 | 1.2494 | 0.7460 | 0.7344 | 0.7473 | 0.7460 |
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+ | 1.811 | 7.5342 | 550 | 1.0760 | 0.7302 | 0.7242 | 0.7563 | 0.7302 |
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+ | 1.4184 | 8.2192 | 600 | 0.9448 | 0.7937 | 0.7878 | 0.8223 | 0.7937 |
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+ | 1.1262 | 8.9041 | 650 | 0.8517 | 0.7937 | 0.7871 | 0.8000 | 0.7937 |
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+ | 0.7899 | 9.5890 | 700 | 0.8264 | 0.8016 | 0.7904 | 0.7993 | 0.8016 |
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+ | 0.4857 | 10.2740 | 750 | 0.7620 | 0.8333 | 0.8275 | 0.8360 | 0.8333 |
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+ | 0.439 | 10.9589 | 800 | 0.7612 | 0.8175 | 0.8099 | 0.8282 | 0.8175 |
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+ | 0.3147 | 11.6438 | 850 | 0.7215 | 0.8175 | 0.8136 | 0.8211 | 0.8175 |
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+ | 0.2098 | 12.3288 | 900 | 0.7429 | 0.8095 | 0.8039 | 0.8219 | 0.8095 |
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+ | 0.1702 | 13.0137 | 950 | 0.7309 | 0.8095 | 0.8039 | 0.8244 | 0.8095 |
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+ | 0.1215 | 13.6986 | 1000 | 0.7320 | 0.8175 | 0.8154 | 0.8327 | 0.8175 |
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+ | 0.0812 | 14.3836 | 1050 | 0.7449 | 0.8175 | 0.8113 | 0.8286 | 0.8175 |
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+ | 0.0693 | 15.0685 | 1100 | 0.7303 | 0.8175 | 0.8126 | 0.8233 | 0.8175 |
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+ | 0.0728 | 15.7534 | 1150 | 0.7449 | 0.8175 | 0.8136 | 0.8277 | 0.8175 |
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+ | 0.0321 | 16.4384 | 1200 | 0.7413 | 0.8175 | 0.8126 | 0.8233 | 0.8175 |
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+ | 0.0662 | 17.1233 | 1250 | 0.7583 | 0.8175 | 0.8136 | 0.8277 | 0.8175 |
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+ | 0.0596 | 17.8082 | 1300 | 0.7504 | 0.8175 | 0.8136 | 0.8277 | 0.8175 |
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+ | 0.0216 | 18.4932 | 1350 | 0.7611 | 0.8175 | 0.8136 | 0.8277 | 0.8175 |
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+ | 0.0353 | 19.1781 | 1400 | 0.7522 | 0.8175 | 0.8136 | 0.8277 | 0.8175 |
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+ | 0.0348 | 19.8630 | 1450 | 0.7560 | 0.8175 | 0.8136 | 0.8277 | 0.8175 |
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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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