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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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base_model: sentence-transformers/all-mpnet-base-v2 |
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model-index: |
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- name: action-policy-plans-classifier |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# action-policy-plans-classifier |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6839 |
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- Precision Micro: 0.7089 |
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- Precision Weighted: 0.7043 |
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- Precision Samples: 0.4047 |
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- Recall Micro: 0.7066 |
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- Recall Weighted: 0.7066 |
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- Recall Samples: 0.4047 |
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- F1-score: 0.4041 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2.915e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 300 |
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- num_epochs: 7 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision Micro | Precision Weighted | Precision Samples | Recall Micro | Recall Weighted | Recall Samples | F1-score | |
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|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:-----------------:|:------------:|:---------------:|:--------------:|:--------:| |
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| 0.7333 | 1.0 | 253 | 0.5828 | 0.625 | 0.6422 | 0.4047 | 0.7098 | 0.7098 | 0.4065 | 0.4047 | |
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| 0.5905 | 2.0 | 506 | 0.5593 | 0.6292 | 0.6318 | 0.4437 | 0.7760 | 0.7760 | 0.4446 | 0.4434 | |
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| 0.4934 | 3.0 | 759 | 0.5269 | 0.6630 | 0.6637 | 0.4319 | 0.7571 | 0.7571 | 0.4347 | 0.4325 | |
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| 0.4018 | 4.0 | 1012 | 0.5645 | 0.6449 | 0.6479 | 0.4456 | 0.7792 | 0.7792 | 0.4465 | 0.4453 | |
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| 0.3235 | 5.0 | 1265 | 0.6101 | 0.6964 | 0.6929 | 0.4220 | 0.7382 | 0.7382 | 0.4229 | 0.4217 | |
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| 0.2638 | 6.0 | 1518 | 0.6692 | 0.6888 | 0.6841 | 0.4111 | 0.7192 | 0.7192 | 0.4120 | 0.4108 | |
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| 0.2197 | 7.0 | 1771 | 0.6839 | 0.7089 | 0.7043 | 0.4047 | 0.7066 | 0.7066 | 0.4047 | 0.4041 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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