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scibert_ner_drugname

Token Classification
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End of training

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  1. README.md +19 -14
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. runs/Mar14_15-40-27_d3f7685783b3/events.out.tfevents.1710430828.d3f7685783b3.172.0 +3 -0
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  23. training_args.bin +2 -2
README.md CHANGED
@@ -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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1491
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- - Precision: 0.7468
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- - Recall: 0.8676
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- - F1: 0.8027
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- - Accuracy: 0.9747
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  ## Model description
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@@ -48,22 +48,27 @@ The following hyperparameters were used during training:
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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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- | 0.1769 | 1.0 | 51 | 0.2158 | 0.3981 | 0.6029 | 0.4795 | 0.9489 |
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- | 0.1079 | 2.0 | 102 | 0.1557 | 0.6506 | 0.7941 | 0.7152 | 0.9693 |
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- | 0.0276 | 3.0 | 153 | 0.1509 | 0.7037 | 0.8382 | 0.7651 | 0.9723 |
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- | 0.0569 | 4.0 | 204 | 0.1476 | 0.7407 | 0.8824 | 0.8054 | 0.9741 |
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- | 0.0119 | 5.0 | 255 | 0.1491 | 0.7468 | 0.8676 | 0.8027 | 0.9747 |
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.37.2
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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
 
19
 
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  This model is a fine-tuned version of [allenai/scibert_scivocab_cased](https://huggingface.co/allenai/scibert_scivocab_cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1243
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+ - Precision: 0.7631
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+ - Recall: 0.8520
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+ - F1: 0.8051
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+ - Accuracy: 0.9722
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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: 10
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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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+ | 0.0733 | 1.0 | 120 | 0.1176 | 0.6466 | 0.7713 | 0.7035 | 0.9583 |
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+ | 0.0069 | 2.0 | 240 | 0.1126 | 0.6757 | 0.7848 | 0.7261 | 0.9654 |
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+ | 0.0521 | 3.0 | 360 | 0.0949 | 0.7461 | 0.8565 | 0.7975 | 0.9707 |
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+ | 0.0217 | 4.0 | 480 | 0.0972 | 0.7171 | 0.8296 | 0.7692 | 0.9718 |
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+ | 0.001 | 5.0 | 600 | 0.1111 | 0.7422 | 0.8520 | 0.7933 | 0.9707 |
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+ | 0.0044 | 6.0 | 720 | 0.1138 | 0.7664 | 0.8386 | 0.8009 | 0.9715 |
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+ | 0.0011 | 7.0 | 840 | 0.1155 | 0.7449 | 0.8251 | 0.7830 | 0.9699 |
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+ | 0.0006 | 8.0 | 960 | 0.1213 | 0.7344 | 0.8430 | 0.7850 | 0.9716 |
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+ | 0.0289 | 9.0 | 1080 | 0.1238 | 0.7661 | 0.8520 | 0.8068 | 0.9718 |
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+ | 0.0096 | 10.0 | 1200 | 0.1243 | 0.7631 | 0.8520 | 0.8051 | 0.9722 |
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  ### Framework versions
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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  - Tokenizers 0.15.2
config.json CHANGED
@@ -32,7 +32,7 @@
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  "pad_token_id": 0,
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  "position_embedding_type": "absolute",
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- "transformers_version": "4.37.2",
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  "vocab_size": 31116
 
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  "position_embedding_type": "absolute",
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  "torch_dtype": "float32",
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  "type_vocab_size": 2,
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