update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: IKT_classifier_economywide_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_economywide_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: 0.1819
+- Precision Weighted: 0.9628
+- Precision Macro: 0.9639
+- Recall Weighted: 0.9623
+- Recall Samples: 0.9606
+- F1-score: 0.9619
+- Accuracy: 0.9623
+
+## 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: 4.427532456702983e-05
+- train_batch_size: 3
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 6
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100.0
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision Weighted | Precision Macro | Recall Weighted | Recall Samples | F1-score | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:---------------:|:--------------:|:--------:|:--------:|
+| No log        | 1.0   | 159  | 0.1640          | 0.9628             | 0.9639          | 0.9623          | 0.9606         | 0.9619   | 0.9623   |
+| No log        | 2.0   | 318  | 0.2042          | 0.9531             | 0.9521          | 0.9528          | 0.9533         | 0.9526   | 0.9528   |
+| No log        | 3.0   | 477  | 0.2298          | 0.9457             | 0.9479          | 0.9434          | 0.9402         | 0.9427   | 0.9434   |
+| 0.1907        | 4.0   | 636  | 0.1582          | 0.9718             | 0.9723          | 0.9717          | 0.9708         | 0.9715   | 0.9717   |
+| 0.1907        | 5.0   | 795  | 0.1819          | 0.9628             | 0.9639          | 0.9623          | 0.9606         | 0.9619   | 0.9623   |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3