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--- |
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license: apache-2.0 |
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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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model-index: |
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- name: verizon_model1 |
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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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# verizon_model1 |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0242 |
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- Accuracy: 1.0 |
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- F1: 1.0 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 1.458 | 1.0 | 8 | 1.1774 | 0.7451 | 0.6817 | |
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| 1.1574 | 2.0 | 16 | 0.8376 | 0.7843 | 0.6934 | |
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| 0.8281 | 3.0 | 24 | 0.6155 | 0.8627 | 0.8055 | |
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| 0.6272 | 4.0 | 32 | 0.4462 | 0.8824 | 0.8493 | |
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| 0.4532 | 5.0 | 40 | 0.3344 | 0.9216 | 0.9111 | |
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| 0.3607 | 6.0 | 48 | 0.2535 | 1.0 | 1.0 | |
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| 0.2153 | 7.0 | 56 | 0.1961 | 0.9804 | 0.9800 | |
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| 0.1704 | 8.0 | 64 | 0.1489 | 1.0 | 1.0 | |
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| 0.1238 | 9.0 | 72 | 0.1116 | 1.0 | 1.0 | |
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| 0.0998 | 10.0 | 80 | 0.0841 | 1.0 | 1.0 | |
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| 0.097 | 11.0 | 88 | 0.0642 | 1.0 | 1.0 | |
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| 0.0751 | 12.0 | 96 | 0.0510 | 1.0 | 1.0 | |
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| 0.0583 | 13.0 | 104 | 0.0421 | 1.0 | 1.0 | |
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| 0.0422 | 14.0 | 112 | 0.0350 | 1.0 | 1.0 | |
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| 0.037 | 15.0 | 120 | 0.0307 | 1.0 | 1.0 | |
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| 0.0354 | 16.0 | 128 | 0.0282 | 1.0 | 1.0 | |
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| 0.0336 | 17.0 | 136 | 0.0265 | 1.0 | 1.0 | |
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| 0.0316 | 18.0 | 144 | 0.0252 | 1.0 | 1.0 | |
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| 0.0341 | 19.0 | 152 | 0.0244 | 1.0 | 1.0 | |
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| 0.027 | 20.0 | 160 | 0.0242 | 1.0 | 1.0 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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