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--- |
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license: mit |
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base_model: prajjwal1/bert-tiny |
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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: I04-PC |
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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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# I04-PC |
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This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0916 |
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- Accuracy: 0.98 |
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- F1: 0.9899 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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| No log | 0.01 | 50 | 0.6723 | 0.66 | 0.6376 | |
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| No log | 0.02 | 100 | 0.5802 | 0.71 | 0.7065 | |
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| No log | 0.03 | 150 | 0.4534 | 0.87 | 0.8701 | |
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| No log | 0.04 | 200 | 0.3370 | 0.88 | 0.88 | |
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| No log | 0.05 | 250 | 0.2473 | 0.94 | 0.9394 | |
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| No log | 0.06 | 300 | 0.2231 | 0.93 | 0.9295 | |
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| No log | 0.07 | 350 | 0.1813 | 0.94 | 0.9394 | |
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| No log | 0.08 | 400 | 0.1519 | 0.96 | 0.9599 | |
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| No log | 0.09 | 450 | 0.1526 | 0.96 | 0.9599 | |
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| 0.3852 | 0.1 | 500 | 0.1554 | 0.96 | 0.9599 | |
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| 0.3852 | 0.11 | 550 | 0.1495 | 0.96 | 0.9599 | |
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| 0.3852 | 0.12 | 600 | 0.1206 | 0.96 | 0.9599 | |
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| 0.3852 | 0.13 | 650 | 0.1013 | 0.96 | 0.9599 | |
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| 0.3852 | 0.14 | 700 | 0.0592 | 0.99 | 0.9900 | |
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| 0.3852 | 0.15 | 750 | 0.0583 | 0.99 | 0.9900 | |
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| 0.3852 | 0.16 | 800 | 0.0551 | 0.99 | 0.9900 | |
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| 0.3852 | 0.17 | 850 | 0.0540 | 0.99 | 0.9900 | |
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| 0.3852 | 0.18 | 900 | 0.0539 | 0.99 | 0.9900 | |
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| 0.3852 | 0.19 | 950 | 0.0537 | 0.99 | 0.9900 | |
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| 0.1428 | 0.2 | 1000 | 0.0533 | 0.99 | 0.9900 | |
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| 0.1428 | 0.2 | 1050 | 0.0528 | 0.99 | 0.9900 | |
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| 0.1428 | 0.21 | 1100 | 0.0510 | 0.99 | 0.9900 | |
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| 0.1428 | 0.22 | 1150 | 0.0524 | 0.99 | 0.9900 | |
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| 0.1428 | 0.23 | 1200 | 0.0524 | 0.99 | 0.9900 | |
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| 0.1428 | 0.24 | 1250 | 0.0510 | 0.99 | 0.9900 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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