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eeshclusive
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scibert-finetuned-ner

Token Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [allenai/scibert_scivocab_cased](https://huggingface.co/allenai/scibert_scivocab_cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4445
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- - Precision: 0.3974
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- - Recall: 0.3404
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- - F1: 0.3667
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- - Accuracy: 0.9140
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  ## Model description
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@@ -54,16 +54,16 @@ The following hyperparameters were used during training:
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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 | 121 | 0.5694 | 0.0808 | 0.0411 | 0.0545 | 0.8648 |
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- | No log | 2.0 | 242 | 0.4878 | 0.3169 | 0.1277 | 0.1820 | 0.9020 |
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- | No log | 3.0 | 363 | 0.4121 | 0.3422 | 0.2199 | 0.2677 | 0.9097 |
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- | No log | 4.0 | 484 | 0.4240 | 0.4273 | 0.2624 | 0.3251 | 0.9147 |
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- | 0.4235 | 5.0 | 605 | 0.3974 | 0.4187 | 0.2922 | 0.3442 | 0.9159 |
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- | 0.4235 | 6.0 | 726 | 0.4125 | 0.4146 | 0.3064 | 0.3524 | 0.9140 |
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- | 0.4235 | 7.0 | 847 | 0.4235 | 0.3713 | 0.3191 | 0.3432 | 0.9136 |
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- | 0.4235 | 8.0 | 968 | 0.4330 | 0.3794 | 0.3348 | 0.3557 | 0.9132 |
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- | 0.1633 | 9.0 | 1089 | 0.4481 | 0.3926 | 0.3319 | 0.3597 | 0.9133 |
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- | 0.1633 | 10.0 | 1210 | 0.4445 | 0.3974 | 0.3404 | 0.3667 | 0.9140 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [allenai/scibert_scivocab_cased](https://huggingface.co/allenai/scibert_scivocab_cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3459
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+ - Precision: 0.5666
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+ - Recall: 0.5191
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+ - F1: 0.5418
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+ - Accuracy: 0.9363
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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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+ | No log | 1.0 | 121 | 0.3648 | 0.3157 | 0.3390 | 0.3269 | 0.8945 |
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+ | No log | 2.0 | 242 | 0.3177 | 0.5280 | 0.3348 | 0.4097 | 0.9253 |
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+ | No log | 3.0 | 363 | 0.2599 | 0.5143 | 0.4326 | 0.4700 | 0.9315 |
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+ | No log | 4.0 | 484 | 0.2825 | 0.5360 | 0.4227 | 0.4726 | 0.9336 |
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+ | 0.2574 | 5.0 | 605 | 0.2968 | 0.5473 | 0.4922 | 0.5183 | 0.9350 |
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+ | 0.2574 | 6.0 | 726 | 0.3193 | 0.5857 | 0.4894 | 0.5332 | 0.9377 |
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+ | 0.2574 | 7.0 | 847 | 0.3327 | 0.5513 | 0.4879 | 0.5177 | 0.9356 |
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+ | 0.2574 | 8.0 | 968 | 0.3315 | 0.5658 | 0.5121 | 0.5376 | 0.9363 |
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+ | 0.0678 | 9.0 | 1089 | 0.3413 | 0.5465 | 0.5163 | 0.5310 | 0.9361 |
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+ | 0.0678 | 10.0 | 1210 | 0.3459 | 0.5666 | 0.5191 | 0.5418 | 0.9363 |
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  ### Framework versions