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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: FPB_finetuned_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. -->
# FPB_finetuned_v1
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4649
- Accuracy: 0.9303
- F1: 0.9303
- Precision: 0.9303
- Recall: 0.9303
## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.7905 | 1.0 | 97 | 0.6913 | 0.7504 | 0.7471 | 0.7458 | 0.7504 |
| 0.3516 | 2.0 | 194 | 0.3914 | 0.8476 | 0.8480 | 0.8517 | 0.8476 |
| 0.2545 | 3.0 | 291 | 0.3302 | 0.8882 | 0.8870 | 0.8911 | 0.8882 |
| 0.1225 | 4.0 | 388 | 0.3488 | 0.8723 | 0.8730 | 0.8801 | 0.8723 |
| 0.0674 | 5.0 | 485 | 0.3910 | 0.8970 | 0.8961 | 0.8963 | 0.8970 |
| 0.0458 | 6.0 | 582 | 0.4545 | 0.9028 | 0.9022 | 0.9036 | 0.9028 |
| 0.0963 | 7.0 | 679 | 0.3467 | 0.9100 | 0.9100 | 0.9104 | 0.9100 |
| 0.0781 | 8.0 | 776 | 0.4528 | 0.8999 | 0.8991 | 0.8996 | 0.8999 |
| 0.0961 | 9.0 | 873 | 0.3966 | 0.9042 | 0.9049 | 0.9091 | 0.9042 |
| 0.0643 | 10.0 | 970 | 0.3486 | 0.9158 | 0.9159 | 0.9160 | 0.9158 |
| 0.0521 | 11.0 | 1067 | 0.5745 | 0.8955 | 0.8931 | 0.9030 | 0.8955 |
| 0.0162 | 12.0 | 1164 | 0.4968 | 0.9042 | 0.9047 | 0.9070 | 0.9042 |
| 0.0106 | 13.0 | 1261 | 0.4925 | 0.9158 | 0.9161 | 0.9171 | 0.9158 |
| 0.0056 | 14.0 | 1358 | 0.5128 | 0.9129 | 0.9126 | 0.9149 | 0.9129 |
| 0.0116 | 15.0 | 1455 | 0.4791 | 0.9202 | 0.9199 | 0.9197 | 0.9202 |
| 0.0004 | 16.0 | 1552 | 0.4417 | 0.9216 | 0.9214 | 0.9218 | 0.9216 |
| 0.0121 | 17.0 | 1649 | 0.4378 | 0.9202 | 0.9199 | 0.9205 | 0.9202 |
| 0.0003 | 18.0 | 1746 | 0.4624 | 0.9245 | 0.9245 | 0.9247 | 0.9245 |
| 0.0001 | 19.0 | 1843 | 0.4697 | 0.9274 | 0.9275 | 0.9277 | 0.9274 |
| 0.0001 | 20.0 | 1940 | 0.4649 | 0.9303 | 0.9303 | 0.9303 | 0.9303 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.2
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