update model card README.md

README.md

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+---
+license: apache-2.0
+base_model: sentence-transformers/all-mpnet-base-v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: IKT_classifier_conditional_best
+  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. -->
+
+# IKT_classifier_conditional_best
+
+This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9766
+- Precision Macro: 0.8010
+- Precision Weighted: 0.8078
+- Recall Macro: 0.7928
+- Recall Weighted: 0.8093
+- F1-score: 0.7963
+- Accuracy: 0.8093
+
+## 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: 4.112924307850544e-05
+- train_batch_size: 3
+- eval_batch_size: 3
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 400.0
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision Macro | Precision Weighted | Recall Macro | Recall Weighted | F1-score | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:------------:|:---------------:|:--------:|:--------:|
+| 0.6562        | 1.0   | 696  | 0.5617          | 0.7283          | 0.7423             | 0.7283       | 0.7423          | 0.7283   | 0.7423   |
+| 0.6091        | 2.0   | 1392 | 0.6492          | 0.7345          | 0.7443             | 0.7251       | 0.7474          | 0.7287   | 0.7474   |
+| 0.3892        | 3.0   | 2088 | 0.7730          | 0.7848          | 0.7872             | 0.7612       | 0.7887          | 0.7687   | 0.7887   |
+| 0.2509        | 4.0   | 2784 | 0.9735          | 0.7778          | 0.7937             | 0.7858       | 0.7887          | 0.7807   | 0.7887   |
+| 0.1648        | 5.0   | 3480 | 0.9766          | 0.8010          | 0.8078             | 0.7928       | 0.8093          | 0.7963   | 0.8093   |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3