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---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: pos_final_mono_en
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. -->
# pos_final_mono_en
This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0681
- Precision: 0.9696
- Recall: 0.9714
- F1: 0.9705
- Accuracy: 0.9796
## 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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 40.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 0.99 | 60 | 2.7933 | 0.3216 | 0.0997 | 0.1522 | 0.2833 |
| No log | 1.99 | 120 | 0.3818 | 0.9075 | 0.8989 | 0.9032 | 0.9224 |
| No log | 2.99 | 180 | 0.1156 | 0.9602 | 0.9607 | 0.9605 | 0.9721 |
| No log | 3.99 | 240 | 0.0911 | 0.9634 | 0.9650 | 0.9642 | 0.9748 |
| No log | 4.99 | 300 | 0.0794 | 0.9664 | 0.9679 | 0.9671 | 0.9772 |
| No log | 5.99 | 360 | 0.0741 | 0.9670 | 0.9697 | 0.9683 | 0.9781 |
| No log | 6.99 | 420 | 0.0695 | 0.9683 | 0.9702 | 0.9693 | 0.9787 |
| No log | 7.99 | 480 | 0.0688 | 0.9686 | 0.9700 | 0.9693 | 0.9789 |
| 0.7281 | 8.99 | 540 | 0.0675 | 0.9688 | 0.9703 | 0.9695 | 0.9789 |
| 0.7281 | 9.99 | 600 | 0.0670 | 0.9687 | 0.9705 | 0.9696 | 0.9791 |
| 0.7281 | 10.99 | 660 | 0.0658 | 0.9696 | 0.9702 | 0.9699 | 0.9792 |
| 0.7281 | 11.99 | 720 | 0.0670 | 0.9684 | 0.9715 | 0.9700 | 0.9793 |
| 0.7281 | 12.99 | 780 | 0.0672 | 0.9689 | 0.9711 | 0.9700 | 0.9792 |
| 0.7281 | 13.99 | 840 | 0.0678 | 0.9698 | 0.9708 | 0.9703 | 0.9796 |
| 0.7281 | 14.99 | 900 | 0.0681 | 0.9696 | 0.9714 | 0.9705 | 0.9796 |
| 0.7281 | 15.99 | 960 | 0.0706 | 0.9696 | 0.9711 | 0.9703 | 0.9795 |
| 0.0484 | 16.99 | 1020 | 0.0725 | 0.9694 | 0.9705 | 0.9699 | 0.9793 |
| 0.0484 | 17.99 | 1080 | 0.0735 | 0.9689 | 0.9705 | 0.9697 | 0.9791 |
| 0.0484 | 18.99 | 1140 | 0.0745 | 0.9690 | 0.9705 | 0.9698 | 0.9792 |
| 0.0484 | 19.99 | 1200 | 0.0769 | 0.9690 | 0.9706 | 0.9698 | 0.9791 |
| 0.0484 | 20.99 | 1260 | 0.0797 | 0.9691 | 0.9703 | 0.9697 | 0.9791 |
| 0.0484 | 21.99 | 1320 | 0.0808 | 0.9689 | 0.9705 | 0.9697 | 0.9791 |
| 0.0484 | 22.99 | 1380 | 0.0838 | 0.9691 | 0.9702 | 0.9697 | 0.9791 |
| 0.0484 | 23.99 | 1440 | 0.0861 | 0.9685 | 0.9704 | 0.9695 | 0.9789 |
| 0.0289 | 24.99 | 1500 | 0.0879 | 0.9684 | 0.9698 | 0.9691 | 0.9787 |
| 0.0289 | 25.99 | 1560 | 0.0887 | 0.9684 | 0.9703 | 0.9694 | 0.9789 |
| 0.0289 | 26.99 | 1620 | 0.0910 | 0.9684 | 0.9698 | 0.9691 | 0.9787 |
| 0.0289 | 27.99 | 1680 | 0.0924 | 0.9684 | 0.9697 | 0.9691 | 0.9787 |
| 0.0289 | 28.99 | 1740 | 0.0950 | 0.9693 | 0.9692 | 0.9693 | 0.9788 |
| 0.0289 | 29.99 | 1800 | 0.0962 | 0.9692 | 0.9697 | 0.9694 | 0.9789 |
| 0.0289 | 30.99 | 1860 | 0.0977 | 0.9687 | 0.9699 | 0.9693 | 0.9787 |
| 0.0289 | 31.99 | 1920 | 0.0979 | 0.9688 | 0.9699 | 0.9694 | 0.9788 |
| 0.0289 | 32.99 | 1980 | 0.1000 | 0.9687 | 0.9698 | 0.9692 | 0.9788 |
| 0.018 | 33.99 | 2040 | 0.1021 | 0.9688 | 0.9698 | 0.9693 | 0.9788 |
| 0.018 | 34.99 | 2100 | 0.1037 | 0.9687 | 0.9701 | 0.9694 | 0.9788 |
| 0.018 | 35.99 | 2160 | 0.1035 | 0.9688 | 0.9703 | 0.9696 | 0.9790 |
| 0.018 | 36.99 | 2220 | 0.1042 | 0.9688 | 0.9700 | 0.9694 | 0.9789 |
| 0.018 | 37.99 | 2280 | 0.1053 | 0.9685 | 0.9699 | 0.9692 | 0.9787 |
| 0.018 | 38.99 | 2340 | 0.1052 | 0.9689 | 0.9700 | 0.9695 | 0.9789 |
| 0.018 | 39.99 | 2400 | 0.1054 | 0.9688 | 0.9700 | 0.9694 | 0.9788 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.12.0
- Datasets 2.18.0
- Tokenizers 0.13.2
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