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action-policy-plans-classifier
ppsingh/action-policy-plans-classifier
action-policy-plans-classifier is a text classification model from ppsingh. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- mpnet
- Access
- Public
- Created
- Jun 13, 2023
- Updated
- Jun 13, 2023
- SHA
- 3b776b28
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Model card
From the Hugging Face model README
<!-- 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 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
- Task
- Text Classification
- Library
- transformers
- Type
- mpnet
- License
- apache-2.0
- Created
- Jun 13, 2023
- Updated
- Jun 13, 2023