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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-base-uncased-ft-google
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. -->
# bert-base-uncased-ft-google
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the [steciuk/google](https://huggingface.co/datasets/steciuk/google) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3195
- Accuracy: 0.9105
- F1: 0.9174
and flowing results on the testing set:
- Accuracy: 0.9096
- F1: 0.9161
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3651 | 0.37 | 196 | 0.2641 | 0.8962 | 0.9064 |
| 0.2765 | 0.75 | 392 | 0.2484 | 0.9019 | 0.9099 |
| 0.2349 | 1.12 | 588 | 0.2532 | 0.9133 | 0.9205 |
| 0.2015 | 1.49 | 784 | 0.2692 | 0.9095 | 0.9139 |
| 0.1817 | 1.86 | 980 | 0.2957 | 0.9095 | 0.9180 |
| 0.1683 | 2.24 | 1176 | 0.2941 | 0.9143 | 0.9213 |
| 0.1204 | 2.61 | 1372 | 0.3230 | 0.9143 | 0.9223 |
| 0.1271 | 2.98 | 1568 | 0.3195 | 0.9105 | 0.9174 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
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