google_mobilebert-uncased fold 6
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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: google/mobilebert-uncased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: google_mobilebert-uncased_fold_6
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# google_mobilebert-uncased_fold_6
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This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1170
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- Accuracy: 0.9588
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- F1: 0.9548
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- Precision: 0.9603
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- Recall: 0.9493
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 40
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- eval_batch_size: 40
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.1319 | 1.0 | 15481 | 0.1306 | 0.9502 | 0.9452 | 0.9520 | 0.9386 |
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| 0.0944 | 2.0 | 30962 | 0.1145 | 0.9567 | 0.9525 | 0.9573 | 0.9477 |
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| 0.0772 | 3.0 | 46443 | 0.1170 | 0.9588 | 0.9548 | 0.9603 | 0.9493 |
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### Framework versions
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- Transformers 5.3.0
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- Pytorch 2.10.0+cu128
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- Datasets 4.6.1
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- Tokenizers 0.22.2
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