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--- |
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base_model: google-bert/bert-base-uncased |
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datasets: |
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- wnut_17 |
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library_name: peft |
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license: apache-2.0 |
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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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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: bert-base-uncased-wnut_17 |
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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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# bert-base-uncased-wnut_17 |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co./google-bert/bert-base-uncased) on the wnut_17 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2870 |
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- Precision: 0.4802 |
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- Recall: 0.2132 |
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- F1: 0.2953 |
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- Accuracy: 0.9366 |
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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: 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 | 213 | 0.4305 | 1.0 | 0.0 | 0.0 | 0.9256 | |
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| No log | 2.0 | 426 | 0.3568 | 0.0 | 0.0 | 0.0 | 0.9256 | |
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| 0.496 | 3.0 | 639 | 0.3379 | 0.3495 | 0.0334 | 0.0609 | 0.9277 | |
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| 0.496 | 4.0 | 852 | 0.3166 | 0.3824 | 0.1205 | 0.1832 | 0.9321 | |
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| 0.1935 | 5.0 | 1065 | 0.3034 | 0.3907 | 0.1705 | 0.2374 | 0.9343 | |
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| 0.1935 | 6.0 | 1278 | 0.2956 | 0.4313 | 0.1863 | 0.2602 | 0.9353 | |
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| 0.1935 | 7.0 | 1491 | 0.2941 | 0.4700 | 0.1891 | 0.2697 | 0.9357 | |
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| 0.1717 | 8.0 | 1704 | 0.2960 | 0.4874 | 0.1965 | 0.2801 | 0.9363 | |
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| 0.1717 | 9.0 | 1917 | 0.2882 | 0.4797 | 0.2076 | 0.2898 | 0.9364 | |
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| 0.1594 | 10.0 | 2130 | 0.2870 | 0.4802 | 0.2132 | 0.2953 | 0.9366 | |
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### Framework versions |
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- PEFT 0.12.1.dev0 |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
