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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: my_awesome_model |
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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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# my_awesome_model |
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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: 1.0970 |
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- Accuracy: 0.8681 |
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- F1: 0.8376 |
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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: 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: 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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| No log | 1.0 | 167 | 0.3828 | 0.8501 | 0.8031 | |
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| No log | 2.0 | 334 | 0.4787 | 0.8456 | 0.8275 | |
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| 0.2101 | 3.0 | 501 | 0.6186 | 0.8666 | 0.8367 | |
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| 0.2101 | 4.0 | 668 | 0.7201 | 0.8546 | 0.8265 | |
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| 0.2101 | 5.0 | 835 | 0.7675 | 0.8651 | 0.8346 | |
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| 0.0339 | 6.0 | 1002 | 0.8561 | 0.8681 | 0.8434 | |
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| 0.0339 | 7.0 | 1169 | 0.8898 | 0.8681 | 0.8382 | |
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| 0.0339 | 8.0 | 1336 | 0.9854 | 0.8711 | 0.8436 | |
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| 0.0069 | 9.0 | 1503 | 0.9919 | 0.8711 | 0.8407 | |
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| 0.0069 | 10.0 | 1670 | 1.0695 | 0.8561 | 0.8280 | |
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| 0.0069 | 11.0 | 1837 | 1.0542 | 0.8666 | 0.8349 | |
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| 0.0007 | 12.0 | 2004 | 1.0896 | 0.8681 | 0.8370 | |
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| 0.0007 | 13.0 | 2171 | 1.1001 | 0.8666 | 0.8349 | |
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| 0.0007 | 14.0 | 2338 | 1.0888 | 0.8606 | 0.8312 | |
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| 0.0012 | 15.0 | 2505 | 1.0970 | 0.8681 | 0.8376 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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