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_transport_ghg_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_transport_ghg_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: 0.5948
+- Precision Macro: 0.8995
+- Precision Weighted: 0.8712
+- Recall Macro: 0.8177
+- Recall Weighted: 0.8605
+- F1-score: 0.8456
+- Accuracy: 0.8605
+
+## 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: 6.900299287565753e-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
+- lr_scheduler_warmup_steps: 100.0
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision Macro | Precision Weighted | Recall Macro | Recall Weighted | F1-score | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:------------:|:---------------:|:--------:|:--------:|
+| No log        | 1.0   | 52   | 0.9196          | 0.5132          | 0.6619             | 0.5936       | 0.7674          | 0.5493   | 0.7674   |
+| No log        | 2.0   | 104  | 0.4997          | 0.9079          | 0.8830             | 0.7807       | 0.8605          | 0.8112   | 0.8605   |
+| No log        | 3.0   | 156  | 0.4113          | 0.7992          | 0.8372             | 0.7992       | 0.8372          | 0.7992   | 0.8372   |
+| No log        | 4.0   | 208  | 0.3726          | 0.9186          | 0.8935             | 0.8713       | 0.8837          | 0.8898   | 0.8837   |
+| No log        | 5.0   | 260  | 0.5869          | 0.8687          | 0.8312             | 0.7446       | 0.8140          | 0.7758   | 0.8140   |
+| No log        | 6.0   | 312  | 0.5321          | 0.8463          | 0.8593             | 0.8168       | 0.8605          | 0.8293   | 0.8605   |
+| No log        | 7.0   | 364  | 0.5608          | 0.9149          | 0.8907             | 0.8353       | 0.8837          | 0.8632   | 0.8837   |
+| No log        | 8.0   | 416  | 0.5948          | 0.8995          | 0.8712             | 0.8177       | 0.8605          | 0.8456   | 0.8605   |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3