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abishekcodes
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pii_model

Token Classification
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TensorBoard
Safetensors
distilbert
Generated from Trainer
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End of training

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  1. README.md +18 -11
  2. model.safetensors +1 -1
  3. runs/Aug20_15-12-34_f26f33d537cf/events.out.tfevents.1755703389.f26f33d537cf.4290.1 +3 -0
  4. runs/Aug20_15-36-21_f26f33d537cf/events.out.tfevents.1755704185.f26f33d537cf.4290.2 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -19,9 +19,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0305
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- - Accuracy: 0.9928
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- - F1: 0.9785
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  ## Model description
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@@ -41,20 +41,27 @@ More information needed
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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: 16
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- - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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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- - num_epochs: 3
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.0279 | 1.0 | 2003 | 0.0292 | 0.9912 | 0.9716 |
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- | 0.0135 | 2.0 | 4006 | 0.0282 | 0.9919 | 0.9750 |
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- | 0.0057 | 3.0 | 6009 | 0.0305 | 0.9928 | 0.9785 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0326
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+ - Accuracy: 0.9950
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+ - F1: 0.9873
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  ## Model description
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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: 32
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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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+ - num_epochs: 10
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
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+ | 0.0207 | 1.0 | 1846 | 0.0205 | 0.9938 | 0.9813 |
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+ | 0.01 | 2.0 | 3692 | 0.0222 | 0.9938 | 0.9825 |
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+ | 0.0053 | 3.0 | 5538 | 0.0231 | 0.9946 | 0.9851 |
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+ | 0.0041 | 4.0 | 7384 | 0.0258 | 0.9945 | 0.9852 |
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+ | 0.0026 | 5.0 | 9230 | 0.0262 | 0.9946 | 0.9857 |
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+ | 0.0016 | 6.0 | 11076 | 0.0305 | 0.9946 | 0.9857 |
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+ | 0.0011 | 7.0 | 12922 | 0.0268 | 0.9949 | 0.9866 |
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+ | 0.0009 | 8.0 | 14768 | 0.0299 | 0.9948 | 0.9867 |
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+ | 0.0004 | 9.0 | 16614 | 0.0307 | 0.9949 | 0.9872 |
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+ | 0.0001 | 10.0 | 18460 | 0.0326 | 0.9950 | 0.9873 |
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  ### Framework versions
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