update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+model-index:
+- name: action-policy-plans-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. -->
+
+# action-policy-plans-classifier
+
+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: 0.6839
+- Precision Micro: 0.7089
+- Precision Weighted: 0.7043
+- Precision Samples: 0.4047
+- Recall Micro: 0.7066
+- Recall Weighted: 0.7066
+- Recall Samples: 0.4047
+- F1-score: 0.4041
+
+## 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: 2.915e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 300
+- num_epochs: 7
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision Micro | Precision Weighted | Precision Samples | Recall Micro | Recall Weighted | Recall Samples | F1-score |
+|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:-----------------:|:------------:|:---------------:|:--------------:|:--------:|
+| 0.7333        | 1.0   | 253  | 0.5828          | 0.625           | 0.6422             | 0.4047            | 0.7098       | 0.7098          | 0.4065         | 0.4047   |
+| 0.5905        | 2.0   | 506  | 0.5593          | 0.6292          | 0.6318             | 0.4437            | 0.7760       | 0.7760          | 0.4446         | 0.4434   |
+| 0.4934        | 3.0   | 759  | 0.5269          | 0.6630          | 0.6637             | 0.4319            | 0.7571       | 0.7571          | 0.4347         | 0.4325   |
+| 0.4018        | 4.0   | 1012 | 0.5645          | 0.6449          | 0.6479             | 0.4456            | 0.7792       | 0.7792          | 0.4465         | 0.4453   |
+| 0.3235        | 5.0   | 1265 | 0.6101          | 0.6964          | 0.6929             | 0.4220            | 0.7382       | 0.7382          | 0.4229         | 0.4217   |
+| 0.2638        | 6.0   | 1518 | 0.6692          | 0.6888          | 0.6841             | 0.4111            | 0.7192       | 0.7192          | 0.4120         | 0.4108   |
+| 0.2197        | 7.0   | 1771 | 0.6839          | 0.7089          | 0.7043             | 0.4047            | 0.7066       | 0.7066          | 0.4047         | 0.4041   |
+
+
+### Framework versions
+
+- Transformers 4.28.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.3