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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: distilbert/distilbert-base-cased |
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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: my_awesome_wnut_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_wnut_model |
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This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0832 |
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- Precision: 0.0 |
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- Recall: 0.0 |
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- F1: 0.0 |
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- Accuracy: 0.9821 |
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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: 0.0002 |
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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: 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 | 118 | 0.0767 | 0.0 | 0.0 | 0.0 | 0.9725 | |
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| No log | 2.0 | 236 | 0.0554 | 0.0 | 0.0 | 0.0 | 0.9799 | |
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| No log | 3.0 | 354 | 0.0695 | 0.0 | 0.0 | 0.0 | 0.9799 | |
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| No log | 4.0 | 472 | 0.0762 | 0.0 | 0.0 | 0.0 | 0.9795 | |
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| 0.0497 | 5.0 | 590 | 0.0888 | 0.0 | 0.0 | 0.0 | 0.9804 | |
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| 0.0497 | 6.0 | 708 | 0.0820 | 0.0 | 0.0 | 0.0 | 0.9812 | |
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| 0.0497 | 7.0 | 826 | 0.0877 | 0.0 | 0.0 | 0.0 | 0.9814 | |
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| 0.0497 | 8.0 | 944 | 0.0864 | 0.0 | 0.0 | 0.0 | 0.9815 | |
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| 0.003 | 9.0 | 1062 | 0.0876 | 0.0 | 0.0 | 0.0 | 0.9823 | |
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| 0.003 | 10.0 | 1180 | 0.0832 | 0.0 | 0.0 | 0.0 | 0.9821 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.5.1 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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