dile3/biobert-ner-ncbi

README.md

@@ -3,8 +3,6 @@ library_name: transformers
 base_model: dmis-lab/biobert-base-cased-v1.1
 tags:
 - generated_from_trainer
-datasets:
-- ncbi_disease
 model-index:
 - name: biobert-ner-model
   results: []
@@ -15,17 +13,17 @@ should probably proofread and complete it, then remove this comment. -->
 
 # biobert-ner-model
 
-This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.1](https://huggingface.co/dmis-lab/biobert-base-cased-v1.1) on the ncbi_disease dataset.
+This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.1](https://huggingface.co/dmis-lab/biobert-base-cased-v1.1) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0557
-- Compositemention: {'precision': 0.2765957446808511, 'recall': 0.37142857142857144, 'f1': 0.3170731707317073, 'number': 35}
-- Diseaseclass: {'precision': 0.5, 'recall': 0.6031746031746031, 'f1': 0.5467625899280575, 'number': 126}
-- Modifier: {'precision': 0.7665198237885462, 'recall': 0.8169014084507042, 'f1': 0.7909090909090909, 'number': 213}
-- Specificdisease: {'precision': 0.75625, 'recall': 0.8810679611650486, 'f1': 0.81390134529148, 'number': 412}
-- Overall Precision: 0.6909
-- Overall Recall: 0.7964
-- Overall F1: 0.7400
-- Overall Accuracy: 0.9854
+- Loss: 0.0255
+- Compositemention: {'precision': 0.8108108108108109, 'recall': 0.8571428571428571, 'f1': 0.8333333333333334, 'number': 35}
+- Diseaseclass: {'precision': 0.6277372262773723, 'recall': 0.6825396825396826, 'f1': 0.6539923954372623, 'number': 126}
+- Modifier: {'precision': 0.7520325203252033, 'recall': 0.8644859813084113, 'f1': 0.8043478260869567, 'number': 214}
+- Specificdisease: {'precision': 0.8380952380952381, 'recall': 0.8543689320388349, 'f1': 0.8461538461538461, 'number': 412}
+- Overall Precision: 0.7774
+- Overall Recall: 0.8297
+- Overall F1: 0.8027
+- Overall Accuracy: 0.9944
 
 ## Model description
 
@@ -54,13 +52,13 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Compositemention                                                                                            | Diseaseclass                                                                                              | Modifier                                                                                                 | Specificdisease                                                                                          | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:-----------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 0.0688        | 1.0   | 75   | 0.0687          | {'precision': 0.075, 'recall': 0.08571428571428572, 'f1': 0.08, 'number': 35}                               | {'precision': 0.3684210526315789, 'recall': 0.4444444444444444, 'f1': 0.4028776978417266, 'number': 126}  | {'precision': 0.5581395348837209, 'recall': 0.676056338028169, 'f1': 0.6114649681528661, 'number': 213}  | {'precision': 0.6083788706739527, 'recall': 0.8106796116504854, 'f1': 0.6951092611862643, 'number': 412} | 0.5375            | 0.6832         | 0.6017     | 0.9797           |
-| 0.0416        | 2.0   | 150  | 0.0621          | {'precision': 0.038461538461538464, 'recall': 0.02857142857142857, 'f1': 0.03278688524590164, 'number': 35} | {'precision': 0.3706896551724138, 'recall': 0.3412698412698413, 'f1': 0.3553719008264463, 'number': 126}  | {'precision': 0.6653225806451613, 'recall': 0.7746478873239436, 'f1': 0.7158351409978307, 'number': 213} | {'precision': 0.6208695652173913, 'recall': 0.866504854368932, 'f1': 0.7234042553191489, 'number': 412}  | 0.5865            | 0.7201         | 0.6465     | 0.9817           |
-| 0.0399        | 3.0   | 225  | 0.0537          | {'precision': 0.26666666666666666, 'recall': 0.34285714285714286, 'f1': 0.3, 'number': 35}                  | {'precision': 0.45390070921985815, 'recall': 0.5079365079365079, 'f1': 0.4794007490636704, 'number': 126} | {'precision': 0.7522123893805309, 'recall': 0.7981220657276995, 'f1': 0.7744874715261958, 'number': 213} | {'precision': 0.6927592954990215, 'recall': 0.8592233009708737, 'f1': 0.7670639219934994, 'number': 412} | 0.6501            | 0.7634         | 0.7022     | 0.9848           |
-| 0.0263        | 4.0   | 300  | 0.0548          | {'precision': 0.3125, 'recall': 0.42857142857142855, 'f1': 0.3614457831325301, 'number': 35}                | {'precision': 0.47096774193548385, 'recall': 0.5793650793650794, 'f1': 0.5195729537366549, 'number': 126} | {'precision': 0.776255707762557, 'recall': 0.7981220657276995, 'f1': 0.7870370370370371, 'number': 213}  | {'precision': 0.7433264887063655, 'recall': 0.8786407766990292, 'f1': 0.8053392658509455, 'number': 412} | 0.6821            | 0.7888         | 0.7316     | 0.9852           |
-| 0.0214        | 5.0   | 375  | 0.0557          | {'precision': 0.2765957446808511, 'recall': 0.37142857142857144, 'f1': 0.3170731707317073, 'number': 35}    | {'precision': 0.5, 'recall': 0.6031746031746031, 'f1': 0.5467625899280575, 'number': 126}                 | {'precision': 0.7665198237885462, 'recall': 0.8169014084507042, 'f1': 0.7909090909090909, 'number': 213} | {'precision': 0.75625, 'recall': 0.8810679611650486, 'f1': 0.81390134529148, 'number': 412}              | 0.6909            | 0.7964         | 0.7400     | 0.9854           |
+| Training Loss | Epoch | Step | Validation Loss | Compositemention                                                                                         | Diseaseclass                                                                                             | Modifier                                                                                                 | Specificdisease                                                                                          | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 0.0247        | 1.0   | 717  | 0.0271          | {'precision': 0.3076923076923077, 'recall': 0.34285714285714286, 'f1': 0.3243243243243243, 'number': 35} | {'precision': 0.35909090909090907, 'recall': 0.626984126984127, 'f1': 0.4566473988439306, 'number': 126} | {'precision': 0.6027397260273972, 'recall': 0.822429906542056, 'f1': 0.6956521739130435, 'number': 214}  | {'precision': 0.7126436781609196, 'recall': 0.7524271844660194, 'f1': 0.7319952774498228, 'number': 412} | 0.5852            | 0.7332         | 0.6509     | 0.9912           |
+| 0.0162        | 2.0   | 1434 | 0.0233          | {'precision': 0.7948717948717948, 'recall': 0.8857142857142857, 'f1': 0.8378378378378378, 'number': 35}  | {'precision': 0.5666666666666667, 'recall': 0.5396825396825397, 'f1': 0.5528455284552845, 'number': 126} | {'precision': 0.746938775510204, 'recall': 0.8551401869158879, 'f1': 0.7973856209150327, 'number': 214}  | {'precision': 0.7850877192982456, 'recall': 0.8689320388349514, 'f1': 0.8248847926267281, 'number': 412} | 0.7442            | 0.8132         | 0.7772     | 0.9941           |
+| 0.0031        | 3.0   | 2151 | 0.0219          | {'precision': 0.8157894736842105, 'recall': 0.8857142857142857, 'f1': 0.8493150684931505, 'number': 35}  | {'precision': 0.5572519083969466, 'recall': 0.5793650793650794, 'f1': 0.5680933852140078, 'number': 126} | {'precision': 0.7206477732793523, 'recall': 0.8317757009345794, 'f1': 0.772234273318872, 'number': 214}  | {'precision': 0.8, 'recall': 0.8640776699029126, 'f1': 0.8308051341890316, 'number': 412}                | 0.7410            | 0.8107         | 0.7743     | 0.9943           |
+| 0.002         | 4.0   | 2868 | 0.0236          | {'precision': 0.8648648648648649, 'recall': 0.9142857142857143, 'f1': 0.888888888888889, 'number': 35}   | {'precision': 0.6223776223776224, 'recall': 0.7063492063492064, 'f1': 0.6617100371747212, 'number': 126} | {'precision': 0.7312252964426877, 'recall': 0.8644859813084113, 'f1': 0.7922912205567451, 'number': 214} | {'precision': 0.837708830548926, 'recall': 0.8519417475728155, 'f1': 0.8447653429602887, 'number': 412}  | 0.7711            | 0.8348         | 0.8017     | 0.9945           |
+| 0.004         | 5.0   | 3585 | 0.0255          | {'precision': 0.8108108108108109, 'recall': 0.8571428571428571, 'f1': 0.8333333333333334, 'number': 35}  | {'precision': 0.6277372262773723, 'recall': 0.6825396825396826, 'f1': 0.6539923954372623, 'number': 126} | {'precision': 0.7520325203252033, 'recall': 0.8644859813084113, 'f1': 0.8043478260869567, 'number': 214} | {'precision': 0.8380952380952381, 'recall': 0.8543689320388349, 'f1': 0.8461538461538461, 'number': 412} | 0.7774            | 0.8297         | 0.8027     | 0.9944           |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e3308e862d61734a2d4a64a692b83cd8cd8b803afa6fb271489503e193222b79
+oid sha256:db5fee965a9673599ff913c6d3aa24f1e1d4352604eb21292abde13fe2c4c35e
 size 430929740

tokenizer.json

@@ -2,13 +2,13 @@
   "version": "1.0",
   "truncation": {
     "direction": "Right",
-    "max_length": 512,
+    "max_length": 128,
     "strategy": "LongestFirst",
     "stride": 0
   },
   "padding": {
     "strategy": {
-      "Fixed": 512
+      "Fixed": 128
     },
     "direction": "Right",
     "pad_to_multiple_of": null,