update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- recall
+- precision
+model-index:
+- name: police-lethal-force-classifier
+  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. -->
+
+# police-lethal-force-classifier
+
+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: 0.0087
+- Accuracy: 0.9980
+- F1-score: 0.9964
+- Recall: 0.9965
+- Precision: 0.9963
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1-score | Recall | Precision |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:------:|:---------:|
+| 0.0138        | 1.0   | 12050 | 0.0132          | 0.9973   | 0.9951   | 0.9953 | 0.9949    |
+| 0.0091        | 2.0   | 24100 | 0.0087          | 0.9980   | 0.9964   | 0.9965 | 0.9963    |
+
+
+### Framework versions
+
+- Transformers 4.26.1
+- Pytorch 1.13.1+cu116
+- Datasets 2.10.0
+- Tokenizers 0.13.2