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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: distilBERT_mergeddata_with_preprocessing_grid_search |
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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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# distilBERT_mergeddata_with_preprocessing_grid_search |
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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: 0.1986 |
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- Precision: 0.9664 |
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- Recall: 0.9668 |
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- F1: 0.9665 |
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- Accuracy: 0.9667 |
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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: 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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 225 | 0.1748 | 0.9549 | 0.9514 | 0.9520 | 0.9528 | |
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| No log | 2.0 | 450 | 0.1584 | 0.9567 | 0.9563 | 0.9562 | 0.9567 | |
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| 0.291 | 3.0 | 675 | 0.1553 | 0.9622 | 0.9627 | 0.9622 | 0.9622 | |
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| 0.291 | 4.0 | 900 | 0.1571 | 0.9647 | 0.9651 | 0.9646 | 0.965 | |
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| 0.0501 | 5.0 | 1125 | 0.1747 | 0.9667 | 0.9671 | 0.9666 | 0.9667 | |
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| 0.0501 | 6.0 | 1350 | 0.1887 | 0.9650 | 0.9658 | 0.9653 | 0.9656 | |
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| 0.0111 | 7.0 | 1575 | 0.1862 | 0.9668 | 0.9666 | 0.9665 | 0.9667 | |
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| 0.0111 | 8.0 | 1800 | 0.1985 | 0.9647 | 0.9649 | 0.9647 | 0.965 | |
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| 0.0044 | 9.0 | 2025 | 0.1954 | 0.9658 | 0.9662 | 0.9659 | 0.9661 | |
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| 0.0044 | 10.0 | 2250 | 0.1986 | 0.9664 | 0.9668 | 0.9665 | 0.9667 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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