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README.md +83 -0
all_results.json +37 -0
eval_results.json +31 -0
train_results.json +9 -0
trainer_state.json +838 -0

README.md ADDED Viewed

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+---
+license: mit
+base_model: microsoft/deberta-v3-base
+tags:
+- generated_from_trainer
+model-index:
+- name: deberta-v3-base_finetuned_bluegennx_run2.21_3e
+  results: []
+---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# deberta-v3-base_finetuned_bluegennx_run2.21_3e
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0168
+- Overall Precision: 0.9773
+- Overall Recall: 0.9878
+- Overall F1: 0.9825
+- Overall Accuracy: 0.9959
+- Aadhar Card F1: 0.9866
+- Age F1: 0.9707
+- City F1: 0.9868
+- Country F1: 0.9865
+- Creditcardcvv F1: 0.9888
+- Creditcardnumber F1: 0.9587
+- Date F1: 0.9643
+- Dateofbirth F1: 0.9165
+- Email F1: 0.9894
+- Expirydate F1: 0.9921
+- Organization F1: 0.9917
+- Pan Card F1: 0.9856
+- Person F1: 0.9883
+- Phonenumber F1: 0.9868
+- Pincode F1: 0.9936
+- Secondaryaddress F1: 0.9861
+- State F1: 0.9901
+- Time F1: 0.9821
+- Url F1: 0.9949
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine_with_restarts
+- lr_scheduler_warmup_ratio: 0.2
+- num_epochs: 3
+### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Aadhar Card F1 | Age F1 | City F1 | Country F1 | Creditcardcvv F1 | Creditcardnumber F1 | Date F1 | Dateofbirth F1 | Email F1 | Expirydate F1 | Organization F1 | Pan Card F1 | Person F1 | Phonenumber F1 | Pincode F1 | Secondaryaddress F1 | State F1 | Time F1 | Url F1 |
+|:-------------:|:-----:|:-----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:------:|:-------:|:----------:|:----------------:|:-------------------:|:-------:|:--------------:|:--------:|:-------------:|:---------------:|:-----------:|:---------:|:--------------:|:----------:|:-------------------:|:--------:|:-------:|:------:|
+| 0.0308        | 1.0   | 16005 | 0.0359          | 0.9500            | 0.9755         | 0.9626     | 0.9920           | 0.9350         | 0.9315 | 0.9658  | 0.9706     | 0.9631           | 0.9282              | 0.9251  | 0.8430         | 0.9719   | 0.9842        | 0.9866          | 0.9696      | 0.9772    | 0.9503         | 0.9835     | 0.9680              | 0.9815   | 0.9739  | 0.9845 |
+| 0.0202        | 2.0   | 32010 | 0.0195          | 0.9737            | 0.9836         | 0.9786     | 0.9950           | 0.9756         | 0.9586 | 0.9790  | 0.9826     | 0.9866           | 0.9497              | 0.9593  | 0.9060         | 0.9893   | 0.9872        | 0.9902          | 0.9716      | 0.9875    | 0.9830         | 0.9939     | 0.9831              | 0.9871   | 0.9799  | 0.9927 |
+| 0.0107        | 3.0   | 48015 | 0.0168          | 0.9773            | 0.9878         | 0.9825     | 0.9959           | 0.9866         | 0.9707 | 0.9868  | 0.9865     | 0.9888           | 0.9587              | 0.9643  | 0.9165         | 0.9894   | 0.9921        | 0.9917          | 0.9856      | 0.9883    | 0.9868         | 0.9936     | 0.9861              | 0.9901   | 0.9821  | 0.9949 |
+### Framework versions
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.19.2
+- Tokenizers 0.19.1

all_results.json ADDED Viewed

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+}

eval_results.json ADDED Viewed

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train_results.json ADDED Viewed

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+}

trainer_state.json ADDED Viewed

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