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chintagunta85
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test_ner3

Token Classification
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distilbert
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - pv_dataset
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: test_ner3
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: pv_dataset
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+ type: pv_dataset
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+ config: PVDatasetCorpus
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+ split: train
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+ args: PVDatasetCorpus
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.6698151950718686
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+ - name: Recall
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+ type: recall
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+ value: 0.6499117663801446
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+ - name: F1
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+ type: f1
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+ value: 0.6597133941985438
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9606609586670052
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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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+ # test_ner3
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the pv_dataset dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2983
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+ - Precision: 0.6698
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+ - Recall: 0.6499
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+ - F1: 0.6597
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+ - Accuracy: 0.9607
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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: 2e-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: 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: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.1106 | 1.0 | 1813 | 0.1128 | 0.6050 | 0.5949 | 0.5999 | 0.9565 |
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+ | 0.0705 | 2.0 | 3626 | 0.1190 | 0.6279 | 0.6122 | 0.6200 | 0.9585 |
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+ | 0.0433 | 3.0 | 5439 | 0.1458 | 0.6342 | 0.5983 | 0.6157 | 0.9574 |
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+ | 0.0301 | 4.0 | 7252 | 0.1453 | 0.6305 | 0.6818 | 0.6552 | 0.9594 |
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+ | 0.0196 | 5.0 | 9065 | 0.1672 | 0.6358 | 0.6871 | 0.6605 | 0.9594 |
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+ | 0.0133 | 6.0 | 10878 | 0.1931 | 0.6427 | 0.6138 | 0.6279 | 0.9587 |
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+ | 0.0104 | 7.0 | 12691 | 0.1948 | 0.6657 | 0.6511 | 0.6583 | 0.9607 |
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+ | 0.0081 | 8.0 | 14504 | 0.2243 | 0.6341 | 0.6574 | 0.6455 | 0.9586 |
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+ | 0.0054 | 9.0 | 16317 | 0.2432 | 0.6547 | 0.6318 | 0.6431 | 0.9588 |
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+ | 0.0041 | 10.0 | 18130 | 0.2422 | 0.6717 | 0.6397 | 0.6553 | 0.9605 |
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+ | 0.0041 | 11.0 | 19943 | 0.2415 | 0.6571 | 0.6420 | 0.6495 | 0.9601 |
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+ | 0.0027 | 12.0 | 21756 | 0.2567 | 0.6560 | 0.6590 | 0.6575 | 0.9601 |
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+ | 0.0023 | 13.0 | 23569 | 0.2609 | 0.6640 | 0.6495 | 0.6566 | 0.9606 |
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+ | 0.002 | 14.0 | 25382 | 0.2710 | 0.6542 | 0.6670 | 0.6606 | 0.9598 |
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+ | 0.0012 | 15.0 | 27195 | 0.2766 | 0.6692 | 0.6539 | 0.6615 | 0.9610 |
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+ | 0.001 | 16.0 | 29008 | 0.2938 | 0.6692 | 0.6415 | 0.6551 | 0.9603 |
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+ | 0.0007 | 17.0 | 30821 | 0.2969 | 0.6654 | 0.6490 | 0.6571 | 0.9604 |
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+ | 0.0007 | 18.0 | 32634 | 0.3035 | 0.6628 | 0.6456 | 0.6541 | 0.9601 |
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+ | 0.0007 | 19.0 | 34447 | 0.2947 | 0.6730 | 0.6489 | 0.6607 | 0.9609 |
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+ | 0.0004 | 20.0 | 36260 | 0.2983 | 0.6698 | 0.6499 | 0.6597 | 0.9607 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.21.0
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+ - Pytorch 1.12.0+cu113
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+ - Datasets 2.4.0
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+ - Tokenizers 0.12.1