End of training
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- pytorch_model.bin +1 -1
README.md
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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: []
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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:
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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.
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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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pytorch_model.bin
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size 437425830
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