End of training

README.md

@@ -4,9 +4,6 @@ license: apache-2.0
 base_model: bert-base-uncased
 tags:
 - generated_from_trainer
-- legal
-- India
-- BERT
 metrics:
 - precision
 - recall
@@ -15,8 +12,6 @@ metrics:
 model-index:
 - name: legal_ai_India_ner_results
   results: []
-datasets:
-- opennyaiorg/InLegalNER
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -26,15 +21,15 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1041
-- Precision: 0.7985
-- Recall: 0.8638
-- F1: 0.8298
-- Accuracy: 0.9697
+- Loss: 0.0989
+- Precision: 0.8007
+- Recall: 0.8602
+- F1: 0.8294
+- Accuracy: 0.9700
 
 ## Model description
 
-This model classifies named entities from the Dataset of India supreme court judgements.
+More information needed
 
 ## Intended uses & limitations
 
@@ -42,7 +37,7 @@ More information needed
 
 ## Training and evaluation data
 
-Training and Evaluation Data is taken from the opennyaiorg/INLegalNer dataset
+More information needed
 
 ## Training procedure
 
@@ -61,15 +56,15 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.4662        | 1.0   | 917  | 0.1419          | 0.6784    | 0.7845 | 0.7276 | 0.9533   |
-| 0.1146        | 2.0   | 1834 | 0.1084          | 0.7529    | 0.8508 | 0.7988 | 0.9623   |
-| 0.0711        | 3.0   | 2751 | 0.1015          | 0.8031    | 0.8627 | 0.8318 | 0.9705   |
-| 0.0546        | 4.0   | 3668 | 0.1041          | 0.7985    | 0.8638 | 0.8298 | 0.9697   |
+| 0.4454        | 1.0   | 917  | 0.1342          | 0.6886    | 0.7867 | 0.7344 | 0.9554   |
+| 0.1136        | 2.0   | 1834 | 0.1004          | 0.7818    | 0.8418 | 0.8107 | 0.9665   |
+| 0.0712        | 3.0   | 2751 | 0.0973          | 0.7990    | 0.8551 | 0.8261 | 0.9705   |
+| 0.0535        | 4.0   | 3668 | 0.0989          | 0.8007    | 0.8602 | 0.8294 | 0.9700   |
 
 
 ### Framework versions
 
-- Transformers 4.48.2
+- Transformers 4.48.3
 - Pytorch 2.5.1+cu124
-- Datasets 3.2.0
-- Tokenizers 0.21.0
+- Datasets 3.3.2
+- Tokenizers 0.21.0

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