| --- |
| 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: 0.1642 |
| - Precision Weighted: 0.9530 |
| - Precision Macro: 0.9524 |
| - Recall Weighted: 0.9528 |
| - Recall Samples: 0.9532 |
| - F1-score: 0.9527 |
| - Accuracy: 0.9528 |
| |
| ## 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: 9.375102561418467e-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: 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 | 30 | 0.3847 | 0.9356 | 0.9340 | 0.9340 | 0.9354 | 0.9339 | 0.9340 | |
| | No log | 2.0 | 60 | 0.3545 | 0.8911 | 0.8933 | 0.8868 | 0.8832 | 0.8853 | 0.8868 | |
| | No log | 3.0 | 90 | 0.1387 | 0.9623 | 0.9621 | 0.9623 | 0.9621 | 0.9621 | 0.9623 | |
| | No log | 4.0 | 120 | 0.1840 | 0.9541 | 0.9555 | 0.9528 | 0.9511 | 0.9525 | 0.9528 | |
| | No log | 5.0 | 150 | 0.1642 | 0.9530 | 0.9524 | 0.9528 | 0.9532 | 0.9527 | 0.9528 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.30.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.13.1 |
| - Tokenizers 0.13.3 |
| |
