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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: BT5153-kaggle-sentiment-model-3000-samples |
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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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# BT5153-kaggle-sentiment-model-3000-samples |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6160 |
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- Accuracy: 0.9270 |
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- F1: 0.9288 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 15 |
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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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| 0.2851 | 1.0 | 625 | 0.2058 | 0.9216 | 0.9231 | |
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| 0.1735 | 2.0 | 1250 | 0.2257 | 0.9244 | 0.9258 | |
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| 0.121 | 3.0 | 1875 | 0.2907 | 0.9232 | 0.9251 | |
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| 0.0525 | 4.0 | 2500 | 0.3607 | 0.9194 | 0.9219 | |
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| 0.0381 | 5.0 | 3125 | 0.4109 | 0.9216 | 0.9233 | |
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| 0.0257 | 6.0 | 3750 | 0.4142 | 0.9232 | 0.9244 | |
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| 0.0192 | 7.0 | 4375 | 0.4321 | 0.9230 | 0.9233 | |
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| 0.0126 | 8.0 | 5000 | 0.4745 | 0.9250 | 0.9278 | |
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| 0.01 | 9.0 | 5625 | 0.5053 | 0.9240 | 0.9246 | |
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| 0.0091 | 10.0 | 6250 | 0.5256 | 0.9240 | 0.9267 | |
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| 0.0062 | 11.0 | 6875 | 0.5798 | 0.9246 | 0.9255 | |
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| 0.0033 | 12.0 | 7500 | 0.5935 | 0.9242 | 0.9262 | |
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| 0.0019 | 13.0 | 8125 | 0.5891 | 0.9286 | 0.9303 | |
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| 0.0018 | 14.0 | 8750 | 0.6176 | 0.9266 | 0.9287 | |
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| 0.0001 | 15.0 | 9375 | 0.6160 | 0.9270 | 0.9288 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.2 |
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