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library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: FP_Classifcation-V1
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. -->
# FP_Classifcation-V1
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2940
- Accuracy: 0.9026
- Precision Macro: 0.8742
- Recall Macro: 0.9098
- F1 Macro: 0.8895
## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|
| 1.0869 | 1.0 | 483 | 0.7657 | 0.6792 | 0.6837 | 0.7053 | 0.6710 |
| 0.9801 | 2.0 | 966 | 0.7458 | 0.7507 | 0.7370 | 0.7004 | 0.7055 |
| 0.9227 | 3.0 | 1449 | 0.6545 | 0.7143 | 0.7075 | 0.7831 | 0.6999 |
| 0.7036 | 4.0 | 1932 | 0.5989 | 0.7733 | 0.7476 | 0.8058 | 0.7593 |
| 0.6729 | 5.0 | 2415 | 0.5175 | 0.7830 | 0.7617 | 0.8409 | 0.7753 |
| 0.8200 | 6.0 | 2898 | 0.4929 | 0.7863 | 0.7541 | 0.8398 | 0.7735 |
| 0.7750 | 7.0 | 3381 | 0.4570 | 0.8154 | 0.7830 | 0.8476 | 0.8038 |
| 0.8015 | 8.0 | 3864 | 0.4494 | 0.8384 | 0.8090 | 0.8493 | 0.8243 |
| 0.6326 | 9.0 | 4347 | 0.4928 | 0.8263 | 0.8066 | 0.8151 | 0.8039 |
| 0.7675 | 10.0 | 4830 | 0.4397 | 0.8347 | 0.8021 | 0.8591 | 0.8175 |
| 0.6092 | 11.0 | 5313 | 0.4220 | 0.8554 | 0.8220 | 0.8603 | 0.8352 |
| 0.4704 | 12.0 | 5796 | 0.5017 | 0.8489 | 0.8190 | 0.8564 | 0.8321 |
| 0.6863 | 13.0 | 6279 | 0.4050 | 0.8533 | 0.8123 | 0.8687 | 0.8313 |
| 0.5217 | 14.0 | 6762 | 0.3839 | 0.8473 | 0.8123 | 0.8753 | 0.8296 |
| 0.4879 | 15.0 | 7245 | 0.4319 | 0.8687 | 0.8556 | 0.8531 | 0.8527 |
| 0.5894 | 16.0 | 7728 | 0.4071 | 0.8339 | 0.8098 | 0.8596 | 0.8245 |
| 0.4710 | 17.0 | 8211 | 0.3890 | 0.8622 | 0.8350 | 0.8626 | 0.8453 |
| 0.6325 | 18.0 | 8694 | 0.3555 | 0.8768 | 0.8425 | 0.8848 | 0.8589 |
| 0.6084 | 19.0 | 9177 | 0.3408 | 0.8865 | 0.8524 | 0.8901 | 0.8680 |
| 0.5211 | 20.0 | 9660 | 0.3399 | 0.8812 | 0.8484 | 0.8828 | 0.8627 |
| 0.3481 | 21.0 | 10143 | 0.3592 | 0.8905 | 0.8673 | 0.8818 | 0.8733 |
| 0.6450 | 22.0 | 10626 | 0.3644 | 0.8877 | 0.8632 | 0.8799 | 0.8706 |
| 0.4031 | 23.0 | 11109 | 0.3248 | 0.8962 | 0.8704 | 0.8944 | 0.8813 |
| 0.4193 | 24.0 | 11592 | 0.3284 | 0.8836 | 0.8587 | 0.8806 | 0.8677 |
| 0.4325 | 25.0 | 12075 | 0.3051 | 0.8881 | 0.8622 | 0.8958 | 0.8767 |
| 0.3674 | 26.0 | 12558 | 0.3227 | 0.8861 | 0.8626 | 0.8839 | 0.8713 |
| 0.3794 | 27.0 | 13041 | 0.3084 | 0.8982 | 0.8777 | 0.8920 | 0.8844 |
| 0.3150 | 28.0 | 13524 | 0.3058 | 0.8954 | 0.8680 | 0.8913 | 0.8777 |
| 0.4406 | 29.0 | 14007 | 0.2965 | 0.8877 | 0.8552 | 0.8943 | 0.8700 |
| 0.5185 | 30.0 | 14490 | 0.2986 | 0.9018 | 0.8768 | 0.8992 | 0.8868 |
| 0.5979 | 31.0 | 14973 | 0.3107 | 0.8986 | 0.8741 | 0.8921 | 0.8824 |
| 0.4205 | 32.0 | 15456 | 0.3153 | 0.9018 | 0.8760 | 0.9054 | 0.8882 |
| 0.3071 | 33.0 | 15939 | 0.2935 | 0.9010 | 0.8774 | 0.8998 | 0.8873 |
| 0.2884 | 34.0 | 16422 | 0.2940 | 0.9026 | 0.8742 | 0.9098 | 0.8895 |
| 0.3953 | 35.0 | 16905 | 0.3187 | 0.8970 | 0.8743 | 0.8911 | 0.8808 |
| 0.2838 | 36.0 | 17388 | 0.3100 | 0.9059 | 0.8814 | 0.8995 | 0.8896 |
| 0.3631 | 37.0 | 17871 | 0.3186 | 0.9063 | 0.8841 | 0.9014 | 0.8920 |
| 0.2681 | 38.0 | 18354 | 0.2929 | 0.9087 | 0.8841 | 0.9093 | 0.8951 |
| 0.2766 | 39.0 | 18837 | 0.2944 | 0.9022 | 0.8793 | 0.9006 | 0.8890 |
### Framework versions
- Transformers 5.17.0
- Pytorch 2.11.0+cu128
- Datasets 5.0.1
- Tokenizers 0.23.1
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