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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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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: summerschool-bert-massive |
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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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# summerschool-bert-massive |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8479 |
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- Accuracy: 0.8283 |
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- F1: 0.8139 |
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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: 2 |
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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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| 3.8604 | 0.1389 | 100 | 3.3964 | 0.2720 | 0.2091 | |
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| 3.046 | 0.2778 | 200 | 2.5353 | 0.4870 | 0.3971 | |
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| 2.3977 | 0.4167 | 300 | 2.0141 | 0.6193 | 0.5592 | |
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| 1.9293 | 0.5556 | 400 | 1.6738 | 0.6803 | 0.6328 | |
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| 1.6997 | 0.6944 | 500 | 1.4307 | 0.7334 | 0.6937 | |
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| 1.505 | 0.8333 | 600 | 1.2759 | 0.7772 | 0.7469 | |
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| 1.3531 | 0.9722 | 700 | 1.1656 | 0.7757 | 0.7445 | |
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| 1.1651 | 1.1111 | 800 | 1.0720 | 0.7914 | 0.7707 | |
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| 1.0441 | 1.25 | 900 | 0.9979 | 0.8032 | 0.7838 | |
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| 1.0021 | 1.3889 | 1000 | 0.9496 | 0.8146 | 0.7977 | |
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| 0.9732 | 1.5278 | 1100 | 0.8996 | 0.8278 | 0.8116 | |
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| 0.9025 | 1.6667 | 1200 | 0.8816 | 0.8214 | 0.8053 | |
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| 0.8952 | 1.8056 | 1300 | 0.8612 | 0.8273 | 0.8128 | |
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| 0.8435 | 1.9444 | 1400 | 0.8479 | 0.8283 | 0.8139 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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