| --- |
| license: apache-2.0 |
| base_model: google/canine-s |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: sentence_splitter_final_v2 |
| 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. --> |
|
|
| # sentence_splitter_final_v2 |
| |
| This model is a fine-tuned version of [google/canine-s](https://huggingface.co/google/canine-s) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0000 |
| - Precision: 0.8 |
| - Recall: 1.0 |
| - F1: 0.8889 |
| - Accuracy: 1.0000 |
| |
| ## 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: 2e-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 |
| - num_epochs: 25 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 95 | 0.0037 | 0.0690 | 0.5 | 0.1212 | 0.9988 | |
| | No log | 2.0 | 190 | 0.0022 | 0.0909 | 1.0 | 0.1667 | 0.9993 | |
| | No log | 3.0 | 285 | 0.0014 | 0.1333 | 1.0 | 0.2353 | 0.9995 | |
| | No log | 4.0 | 380 | 0.0010 | 0.1905 | 1.0 | 0.32 | 0.9996 | |
| | No log | 5.0 | 475 | 0.0008 | 0.25 | 1.0 | 0.4 | 0.9997 | |
| | 0.0096 | 6.0 | 570 | 0.0004 | 0.3636 | 1.0 | 0.5333 | 0.9998 | |
| | 0.0096 | 7.0 | 665 | 0.0004 | 0.2222 | 1.0 | 0.3636 | 0.9999 | |
| | 0.0096 | 8.0 | 760 | 0.0002 | 0.4 | 1.0 | 0.5714 | 0.9999 | |
| | 0.0096 | 9.0 | 855 | 0.0003 | 0.1905 | 1.0 | 0.32 | 0.9999 | |
| | 0.0096 | 10.0 | 950 | 0.0003 | 0.2105 | 1.0 | 0.3478 | 0.9999 | |
| | 0.0008 | 11.0 | 1045 | 0.0001 | 0.3333 | 1.0 | 0.5 | 1.0000 | |
| | 0.0008 | 12.0 | 1140 | 0.0001 | 0.5 | 1.0 | 0.6667 | 1.0000 | |
| | 0.0008 | 13.0 | 1235 | 0.0001 | 0.4444 | 1.0 | 0.6154 | 1.0000 | |
| | 0.0008 | 14.0 | 1330 | 0.0000 | 0.8 | 1.0 | 0.8889 | 1.0000 | |
| | 0.0008 | 15.0 | 1425 | 0.0000 | 0.6667 | 1.0 | 0.8 | 1.0000 | |
| | 0.0003 | 16.0 | 1520 | 0.0000 | 0.8 | 1.0 | 0.8889 | 1.0000 | |
| | 0.0003 | 17.0 | 1615 | 0.0000 | 0.8 | 1.0 | 0.8889 | 1.0000 | |
| | 0.0003 | 18.0 | 1710 | 0.0000 | 0.8 | 1.0 | 0.8889 | 1.0000 | |
| | 0.0003 | 19.0 | 1805 | 0.0000 | 0.8 | 1.0 | 0.8889 | 1.0000 | |
| | 0.0003 | 20.0 | 1900 | 0.0000 | 0.8 | 1.0 | 0.8889 | 1.0000 | |
| | 0.0003 | 21.0 | 1995 | 0.0000 | 0.8 | 1.0 | 0.8889 | 1.0000 | |
| | 0.0001 | 22.0 | 2090 | 0.0000 | 0.8 | 1.0 | 0.8889 | 1.0000 | |
| | 0.0001 | 23.0 | 2185 | 0.0000 | 0.8 | 1.0 | 0.8889 | 1.0000 | |
| | 0.0001 | 24.0 | 2280 | 0.0000 | 0.8 | 1.0 | 0.8889 | 1.0000 | |
| | 0.0001 | 25.0 | 2375 | 0.0000 | 0.8 | 1.0 | 0.8889 | 1.0000 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.0 |
| |
