javicorvi/pretoxtm-ner

README.md

@@ -14,15 +14,15 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2356
-- Study Test: {'precision': 0.8107098381070984, 'recall': 0.9054242002781642, 'f1': 0.8554533508541393, 'number': 719}
-- Manifestation: {'precision': 0.8428571428571429, 'recall': 0.8966565349544073, 'f1': 0.8689248895434463, 'number': 329}
-- Finding: {'precision': 0.7924263674614306, 'recall': 0.7907627711686495, 'f1': 0.7915936952714535, 'number': 1429}
-- Specimen: {'precision': 0.7935064935064935, 'recall': 0.8427586206896551, 'f1': 0.817391304347826, 'number': 725}
-- Dose: {'precision': 0.8894472361809045, 'recall': 0.9315789473684211, 'f1': 0.910025706940874, 'number': 570}
-- Dose Qualification: {'precision': 0.75, 'recall': 0.7368421052631579, 'f1': 0.743362831858407, 'number': 57}
-- Sex: {'precision': 0.9282296650717703, 'recall': 0.9603960396039604, 'f1': 0.9440389294403893, 'number': 202}
-- Group: {'precision': 0.6992481203007519, 'recall': 0.8303571428571429, 'f1': 0.7591836734693878, 'number': 112}
+- Loss: 0.1892
+- Study Test: {'precision': 0.7680288461538461, 'recall': 0.8887343532684284, 'f1': 0.8239845261121858, 'number': 719}
+- Manifestation: {'precision': 0.8245125348189415, 'recall': 0.8996960486322189, 'f1': 0.8604651162790697, 'number': 329}
+- Finding: {'precision': 0.7699175824175825, 'recall': 0.7844646606018194, 'f1': 0.7771230502599653, 'number': 1429}
+- Specimen: {'precision': 0.8063660477453581, 'recall': 0.8386206896551724, 'f1': 0.8221771467207573, 'number': 725}
+- Dose: {'precision': 0.8887043189368771, 'recall': 0.9385964912280702, 'f1': 0.9129692832764505, 'number': 570}
+- Dose Qualification: {'precision': 0.7419354838709677, 'recall': 0.8070175438596491, 'f1': 0.7731092436974789, 'number': 57}
+- Sex: {'precision': 0.9405940594059405, 'recall': 0.9405940594059405, 'f1': 0.9405940594059405, 'number': 202}
+- Group: {'precision': 0.647887323943662, 'recall': 0.8214285714285714, 'f1': 0.7244094488188976, 'number': 112}
 
 ## Model description
 
@@ -53,14 +53,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Study Test                                                                                               | Manifestation                                                                                            | Finding                                                                                                   | Specimen                                                                                                 | Dose                                                                                                     | Dose Qualification                                                                                      | Sex                                                                                                      | Group                                                                                                    |
 |:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|
-| No log        | 1.0   | 257  | 0.2315          | {'precision': 0.7803680981595092, 'recall': 0.8845618915159944, 'f1': 0.8292046936114733, 'number': 719} | {'precision': 0.8481375358166189, 'recall': 0.8996960486322189, 'f1': 0.8731563421828908, 'number': 329} | {'precision': 0.8012618296529969, 'recall': 0.7109867039888034, 'f1': 0.7534297367445311, 'number': 1429} | {'precision': 0.7451456310679612, 'recall': 0.8468965517241379, 'f1': 0.7927695287282118, 'number': 725} | {'precision': 0.9078498293515358, 'recall': 0.9333333333333333, 'f1': 0.9204152249134948, 'number': 570} | {'precision': 0.703125, 'recall': 0.7894736842105263, 'f1': 0.743801652892562, 'number': 57}            | {'precision': 0.9241706161137441, 'recall': 0.9653465346534653, 'f1': 0.9443099273607748, 'number': 202} | {'precision': 0.625, 'recall': 0.8928571428571429, 'f1': 0.7352941176470589, 'number': 112}              |
-| 0.0608        | 2.0   | 514  | 0.2285          | {'precision': 0.803680981595092, 'recall': 0.9109874826147427, 'f1': 0.8539765319426338, 'number': 719}  | {'precision': 0.846820809248555, 'recall': 0.8905775075987842, 'f1': 0.8681481481481481, 'number': 329}  | {'precision': 0.7780040733197556, 'recall': 0.8019594121763471, 'f1': 0.7898001378359754, 'number': 1429} | {'precision': 0.8052631578947368, 'recall': 0.8441379310344828, 'f1': 0.8242424242424241, 'number': 725} | {'precision': 0.9047619047619048, 'recall': 0.9333333333333333, 'f1': 0.9188255613126078, 'number': 570} | {'precision': 0.7368421052631579, 'recall': 0.7368421052631579, 'f1': 0.7368421052631579, 'number': 57} | {'precision': 0.9289099526066351, 'recall': 0.9702970297029703, 'f1': 0.9491525423728814, 'number': 202} | {'precision': 0.6783216783216783, 'recall': 0.8660714285714286, 'f1': 0.7607843137254903, 'number': 112} |
-| 0.0608        | 3.0   | 771  | 0.2356          | {'precision': 0.8107098381070984, 'recall': 0.9054242002781642, 'f1': 0.8554533508541393, 'number': 719} | {'precision': 0.8428571428571429, 'recall': 0.8966565349544073, 'f1': 0.8689248895434463, 'number': 329} | {'precision': 0.7924263674614306, 'recall': 0.7907627711686495, 'f1': 0.7915936952714535, 'number': 1429} | {'precision': 0.7935064935064935, 'recall': 0.8427586206896551, 'f1': 0.817391304347826, 'number': 725}  | {'precision': 0.8894472361809045, 'recall': 0.9315789473684211, 'f1': 0.910025706940874, 'number': 570}  | {'precision': 0.75, 'recall': 0.7368421052631579, 'f1': 0.743362831858407, 'number': 57}                | {'precision': 0.9282296650717703, 'recall': 0.9603960396039604, 'f1': 0.9440389294403893, 'number': 202} | {'precision': 0.6992481203007519, 'recall': 0.8303571428571429, 'f1': 0.7591836734693878, 'number': 112} |
+| No log        | 1.0   | 257  | 0.2128          | {'precision': 0.7071759259259259, 'recall': 0.8497913769123783, 'f1': 0.7719519898926089, 'number': 719} | {'precision': 0.7883597883597884, 'recall': 0.9057750759878419, 'f1': 0.842998585572843, 'number': 329}  | {'precision': 0.7293080054274084, 'recall': 0.7522743177046886, 'f1': 0.74061315880124, 'number': 1429}   | {'precision': 0.7443609022556391, 'recall': 0.8193103448275862, 'f1': 0.7800393959290873, 'number': 725} | {'precision': 0.7741433021806854, 'recall': 0.8719298245614036, 'f1': 0.8201320132013201, 'number': 570} | {'precision': 0.7272727272727273, 'recall': 0.5614035087719298, 'f1': 0.6336633663366337, 'number': 57} | {'precision': 0.9215686274509803, 'recall': 0.9306930693069307, 'f1': 0.9261083743842364, 'number': 202} | {'precision': 0.5673758865248227, 'recall': 0.7142857142857143, 'f1': 0.6324110671936759, 'number': 112} |
+| 0.2683        | 2.0   | 514  | 0.1918          | {'precision': 0.7720144752714113, 'recall': 0.8901251738525731, 'f1': 0.82687338501292, 'number': 719}   | {'precision': 0.803763440860215, 'recall': 0.9088145896656535, 'f1': 0.8530670470756062, 'number': 329}  | {'precision': 0.7732474964234621, 'recall': 0.7564730580825753, 'f1': 0.7647683056243367, 'number': 1429} | {'precision': 0.7907894736842105, 'recall': 0.8289655172413793, 'f1': 0.8094276094276094, 'number': 725} | {'precision': 0.8778877887788779, 'recall': 0.9333333333333333, 'f1': 0.9047619047619047, 'number': 570} | {'precision': 0.746031746031746, 'recall': 0.8245614035087719, 'f1': 0.7833333333333334, 'number': 57}  | {'precision': 0.945, 'recall': 0.9356435643564357, 'f1': 0.9402985074626865, 'number': 202}              | {'precision': 0.6298701298701299, 'recall': 0.8660714285714286, 'f1': 0.7293233082706767, 'number': 112} |
+| 0.2683        | 3.0   | 771  | 0.1892          | {'precision': 0.7680288461538461, 'recall': 0.8887343532684284, 'f1': 0.8239845261121858, 'number': 719} | {'precision': 0.8245125348189415, 'recall': 0.8996960486322189, 'f1': 0.8604651162790697, 'number': 329} | {'precision': 0.7699175824175825, 'recall': 0.7844646606018194, 'f1': 0.7771230502599653, 'number': 1429} | {'precision': 0.8063660477453581, 'recall': 0.8386206896551724, 'f1': 0.8221771467207573, 'number': 725} | {'precision': 0.8887043189368771, 'recall': 0.9385964912280702, 'f1': 0.9129692832764505, 'number': 570} | {'precision': 0.7419354838709677, 'recall': 0.8070175438596491, 'f1': 0.7731092436974789, 'number': 57} | {'precision': 0.9405940594059405, 'recall': 0.9405940594059405, 'f1': 0.9405940594059405, 'number': 202} | {'precision': 0.647887323943662, 'recall': 0.8214285714285714, 'f1': 0.7244094488188976, 'number': 112}  |
 
 
 ### Framework versions
 
-- Transformers 4.33.3
-- Pytorch 2.0.1+cu118
-- Datasets 2.14.5
-- Tokenizers 0.13.3
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

config.json

@@ -57,7 +57,7 @@
   "pad_token_id": 0,
   "position_embedding_type": "absolute",
   "torch_dtype": "float32",
-  "transformers_version": "4.33.3",
+  "transformers_version": "4.35.2",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 28996

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:66fddf6e6b9566751e924cea133c1eb69bfbeb4b592fdd68c4ce7a12c45c6922
+size 430954348

runs/Dec14_12-04-36_a2e3dc378379/events.out.tfevents.1702555486.a2e3dc378379.314.0

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a89f5185f988d6434a4e5f262739a840e2fee821d795a6f8e81d17590dd52bdf
+size 6351

tokenizer_config.json

@@ -1,4 +1,46 @@
 {
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
   "clean_up_tokenization_spaces": true,
   "cls_token": "[CLS]",
   "do_basic_tokenize": true,

training_args.bin

@@ -1,3 +1,3 @@
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-size 4027
+oid sha256:64aad2cb95f982a10ed814caf6eaa6ed663766f0862118816a8410cab546e991
+size 4536