End of training

README.md

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+---
+license: mit
+base_model: law-ai/InLegalBERT
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: IndianLegalBERT
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# IndianLegalBERT
+
+This model is a fine-tuned version of [law-ai/InLegalBERT](https://huggingface.co/law-ai/InLegalBERT) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2872
+- Accuracy: 0.8218
+- Precision: 0.8227
+- Recall: 0.8218
+- Precision Macro: 0.7823
+- Recall Macro: 0.7855
+- Macro Fpr: 0.0158
+- Weighted Fpr: 0.0152
+- Weighted Specificity: 0.9773
+- Macro Specificity: 0.9866
+- Weighted Sensitivity: 0.8218
+- Macro Sensitivity: 0.7855
+- F1 Micro: 0.8218
+- F1 Macro: 0.7809
+- F1 Weighted: 0.8211
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Precision Macro | Recall Macro | Macro Fpr | Weighted Fpr | Weighted Specificity | Macro Specificity | Weighted Sensitivity | Macro Sensitivity | F1 Micro | F1 Macro | F1 Weighted |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---------------:|:------------:|:---------:|:------------:|:--------------------:|:-----------------:|:--------------------:|:-----------------:|:--------:|:--------:|:-----------:|
+| 1.1031        | 1.0   | 643  | 0.6873          | 0.7854   | 0.7628    | 0.7854 | 0.5923          | 0.6107       | 0.0201    | 0.0191       | 0.9691               | 0.9836            | 0.7854               | 0.6107            | 0.7854   | 0.5863   | 0.7674      |
+| 0.5953        | 2.0   | 1286 | 0.6741          | 0.8195   | 0.8135    | 0.8195 | 0.7481          | 0.7363       | 0.0162    | 0.0155       | 0.9753               | 0.9863            | 0.8195               | 0.7363            | 0.8195   | 0.7377   | 0.8153      |
+| 0.4673        | 3.0   | 1929 | 0.7955          | 0.8242   | 0.8206    | 0.8242 | 0.7588          | 0.7421       | 0.0157    | 0.0150       | 0.9749               | 0.9866            | 0.8242               | 0.7421            | 0.8242   | 0.7433   | 0.8204      |
+| 0.2292        | 4.0   | 2572 | 0.8666          | 0.8280   | 0.8297    | 0.8280 | 0.7945          | 0.7864       | 0.0151    | 0.0146       | 0.9786               | 0.9871            | 0.8280               | 0.7864            | 0.8280   | 0.7840   | 0.8270      |
+| 0.1583        | 5.0   | 3215 | 0.9898          | 0.8335   | 0.8348    | 0.8335 | 0.8115          | 0.7893       | 0.0147    | 0.0141       | 0.9778               | 0.9874            | 0.8335               | 0.7893            | 0.8335   | 0.7926   | 0.8308      |
+| 0.0975        | 6.0   | 3858 | 1.1179          | 0.8218   | 0.8260    | 0.8218 | 0.8185          | 0.7573       | 0.0158    | 0.0152       | 0.9781               | 0.9867            | 0.8218               | 0.7573            | 0.8218   | 0.7656   | 0.8203      |
+| 0.0529        | 7.0   | 4501 | 1.1545          | 0.8211   | 0.8205    | 0.8211 | 0.7916          | 0.7691       | 0.0160    | 0.0153       | 0.9758               | 0.9865            | 0.8211               | 0.7691            | 0.8211   | 0.7773   | 0.8203      |
+| 0.0184        | 8.0   | 5144 | 1.2160          | 0.8234   | 0.8248    | 0.8234 | 0.7770          | 0.7829       | 0.0157    | 0.0151       | 0.9774               | 0.9867            | 0.8234               | 0.7829            | 0.8234   | 0.7771   | 0.8229      |
+| 0.0186        | 9.0   | 5787 | 1.2777          | 0.8226   | 0.8244    | 0.8226 | 0.7882          | 0.7851       | 0.0157    | 0.0152       | 0.9774               | 0.9867            | 0.8226               | 0.7851            | 0.8226   | 0.7827   | 0.8223      |
+| 0.007         | 10.0  | 6430 | 1.2872          | 0.8218   | 0.8227    | 0.8218 | 0.7823          | 0.7855       | 0.0158    | 0.0152       | 0.9773               | 0.9866            | 0.8218               | 0.7855            | 0.8218   | 0.7809   | 0.8211      |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.2
+- Datasets 2.1.0
+- Tokenizers 0.15.2

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