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---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
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. -->
# results
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: 1.8481
- Accuracy: 0.425
- F1: 0.4068
- Precision: 0.4371
- Recall: 0.425
- Mse: 5.314
- Mae: 1.37
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Mse | Mae |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:-----:|
| 1.9914 | 1.0 | 157 | 1.7086 | 0.404 | 0.2561 | 0.3800 | 0.404 | 10.332 | 1.95 |
| 1.5651 | 2.0 | 314 | 1.6295 | 0.419 | 0.3343 | 0.4048 | 0.419 | 7.397 | 1.591 |
| 1.3878 | 3.0 | 471 | 1.6456 | 0.421 | 0.3666 | 0.4605 | 0.421 | 6.147 | 1.473 |
| 1.1967 | 4.0 | 628 | 1.7054 | 0.42 | 0.3790 | 0.3598 | 0.42 | 5.874 | 1.44 |
| 1.1002 | 5.0 | 785 | 1.7713 | 0.414 | 0.3896 | 0.3701 | 0.414 | 5.647 | 1.419 |
| 0.9412 | 6.0 | 942 | 1.8481 | 0.425 | 0.4068 | 0.4371 | 0.425 | 5.314 | 1.37 |
| 0.8737 | 7.0 | 1099 | 1.9534 | 0.407 | 0.4007 | 0.4025 | 0.407 | 5.141 | 1.375 |
| 0.757 | 8.0 | 1256 | 2.0153 | 0.401 | 0.3932 | 0.3918 | 0.401 | 5.227 | 1.385 |
| 0.6973 | 9.0 | 1413 | 2.0556 | 0.404 | 0.3979 | 0.4004 | 0.404 | 5.176 | 1.376 |
| 0.6573 | 10.0 | 1570 | 2.0672 | 0.408 | 0.4008 | 0.4003 | 0.408 | 5.179 | 1.373 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
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