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google_mobilebert-uncased fold 3
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---
library_name: transformers
license: apache-2.0
base_model: google/mobilebert-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: google_mobilebert-uncased_fold_3
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# google_mobilebert-uncased_fold_3
This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1173
- Accuracy: 0.9583
- F1: 0.9542
- Precision: 0.9601
- Recall: 0.9485
## 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: 40
- eval_batch_size: 40
- seed: 42
- 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: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1216 | 1.0 | 15481 | 0.1380 | 0.9483 | 0.9423 | 0.9645 | 0.9211 |
| 0.1359 | 2.0 | 30962 | 0.1113 | 0.9568 | 0.9528 | 0.9546 | 0.9510 |
| 0.0927 | 3.0 | 46443 | 0.1173 | 0.9583 | 0.9542 | 0.9601 | 0.9485 |
### Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.6.1
- Tokenizers 0.22.2