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vishnun
/
knowledge-graph-nlp

Token Classification
Transformers
PyTorch
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Safetensors
English
distilbert
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vishnun commited on
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End of training

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Files changed (4) hide show
  1. README.md +11 -13
  2. model.safetensors +1 -1
  3. runs/Feb19_17-21-20_eef45fd72ca1/events.out.tfevents.1708363326.eef45fd72ca1.437.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -11,8 +11,6 @@ metrics:
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  model-index:
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  - name: knowledge-graph-nlp
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  results: []
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- datasets:
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- - vishnun/NLP-KnowledgeGraph
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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
@@ -22,11 +20,11 @@ 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: 0.2719
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- - Precision: 0.8636
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- - Recall: 0.8409
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- - F1: 0.8521
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- - Accuracy: 0.9291
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.1915 | 1.0 | 855 | 0.2499 | 0.8465 | 0.8228 | 0.8345 | 0.9227 |
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- | 0.1345 | 2.0 | 1710 | 0.2609 | 0.8528 | 0.8370 | 0.8448 | 0.9259 |
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- | 0.1078 | 3.0 | 2565 | 0.2664 | 0.8558 | 0.8450 | 0.8504 | 0.9285 |
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- | 0.0949 | 4.0 | 3420 | 0.2719 | 0.8636 | 0.8409 | 0.8521 | 0.9291 |
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  ### Framework versions
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  - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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- - Datasets 2.17.0
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- - Tokenizers 0.15.1
 
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  model-index:
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  - name: knowledge-graph-nlp
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  results: []
 
 
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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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  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: 0.1765
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+ - Precision: 0.9013
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+ - Recall: 0.8807
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+ - F1: 0.8909
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+ - Accuracy: 0.9487
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.2841 | 1.0 | 2316 | 0.2421 | 0.8382 | 0.8124 | 0.8251 | 0.9189 |
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+ | 0.1925 | 2.0 | 4632 | 0.1946 | 0.8752 | 0.8567 | 0.8658 | 0.9373 |
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+ | 0.1539 | 3.0 | 6948 | 0.1815 | 0.8912 | 0.8735 | 0.8822 | 0.9449 |
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+ | 0.1285 | 4.0 | 9264 | 0.1765 | 0.9013 | 0.8807 | 0.8909 | 0.9487 |
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  ### Framework versions
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  - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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