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End of training

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  1. README.md +17 -2
  2. pytorch_model.bin +1 -1
README.md CHANGED
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  base_model: allenai/scibert_scivocab_uncased
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  tags:
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  - generated_from_trainer
 
 
 
 
 
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  model-index:
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  - name: scibert-ner
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  results: []
@@ -13,6 +18,12 @@ should probably proofread and complete it, then remove this comment. -->
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  # scibert-ner
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  This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
 
 
 
 
 
 
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  ## Model description
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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: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 60 | 0.2441 | 0.3858 | 0.1369 | 0.2021 | 0.9461 |
 
 
 
 
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  ### Framework versions
 
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  base_model: allenai/scibert_scivocab_uncased
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  tags:
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  - generated_from_trainer
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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: scibert-ner
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  results: []
 
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  # scibert-ner
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  This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1809
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+ - Precision: 0.4499
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+ - Recall: 0.4637
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+ - F1: 0.4567
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+ - Accuracy: 0.9536
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  ## Model description
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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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 60 | 0.1967 | 0.3563 | 0.3184 | 0.3363 | 0.9509 |
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+ | No log | 2.0 | 120 | 0.1726 | 0.4077 | 0.3855 | 0.3963 | 0.9525 |
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+ | No log | 3.0 | 180 | 0.1723 | 0.4204 | 0.4721 | 0.4447 | 0.9529 |
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+ | No log | 4.0 | 240 | 0.1775 | 0.4248 | 0.4735 | 0.4478 | 0.9526 |
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+ | No log | 5.0 | 300 | 0.1809 | 0.4499 | 0.4637 | 0.4567 | 0.9536 |
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  ### Framework versions
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