Training complete

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9323204419889503
+      value: 0.9174008810572687
     - name: Recall
       type: recall
-      value: 0.9493670886075949
+      value: 0.9083969465648855
     - name: F1
       type: f1
-      value: 0.940766550522648
+      value: 0.9128767123287672
     - name: Accuracy
       type: accuracy
-      value: 0.9986867089931156
+      value: 0.9982350038060345
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the linnaeus dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0069
-- Precision: 0.9323
-- Recall: 0.9494
-- F1: 0.9408
-- Accuracy: 0.9987
+- Loss: 0.0095
+- Precision: 0.9174
+- Recall: 0.9084
+- F1: 0.9129
+- Accuracy: 0.9982
 
 ## Model description
 
@@ -79,14 +79,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0107        | 1.0   | 1492 | 0.0169          | 0.7983    | 0.9409 | 0.8638 | 0.9955   |
-| 0.0023        | 2.0   | 2984 | 0.0073          | 0.9028    | 0.9409 | 0.9215 | 0.9983   |
-| 0.0009        | 3.0   | 4476 | 0.0069          | 0.9323    | 0.9494 | 0.9408 | 0.9987   |
+| 0.0094        | 1.0   | 1492 | 0.0129          | 0.8343    | 0.9280 | 0.8787 | 0.9968   |
+| 0.002         | 2.0   | 2984 | 0.0090          | 0.8928    | 0.9084 | 0.9005 | 0.9979   |
+| 0.0009        | 3.0   | 4476 | 0.0095          | 0.9174    | 0.9084 | 0.9129 | 0.9982   |
 
 
 ### Framework versions
 
-- Transformers 4.33.2
-- Pytorch 2.0.1+cu118
+- Transformers 4.34.0
+- Pytorch 2.1.0+cu121
 - Datasets 2.14.5
-- Tokenizers 0.13.3
+- Tokenizers 0.14.0

config.json

@@ -11,26 +11,14 @@
   "hidden_size": 768,
   "id2label": {
     "0": "O",
-    "1": "B-PER",
-    "2": "I-PER",
-    "3": "B-ORG",
-    "4": "I-ORG",
-    "5": "B-LOC",
-    "6": "I-LOC",
-    "7": "B-MISC",
-    "8": "I-MISC"
+    "1": "B",
+    "2": "I"
   },
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "label2id": {
-    "B-LOC": 5,
-    "B-MISC": 7,
-    "B-ORG": 3,
-    "B-PER": 1,
-    "I-LOC": 6,
-    "I-MISC": 8,
-    "I-ORG": 4,
-    "I-PER": 2,
+    "B": 1,
+    "I": 2,
     "O": 0
   },
   "layer_norm_eps": 1e-12,

pytorch_model.bin

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training_args.bin

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