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--- |
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license: apache-2.0 |
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base_model: bert-base-cased |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: art-bert-base-cased |
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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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# art-bert-base-cased |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.5202 |
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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: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 6.6432 | 3.23 | 100 | 5.8478 | |
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| 5.651 | 6.45 | 200 | 5.5368 | |
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| 5.1511 | 9.68 | 300 | 5.2206 | |
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| 4.77 | 12.9 | 400 | 4.9162 | |
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| 4.449 | 16.13 | 500 | 4.8133 | |
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| 4.18 | 19.35 | 600 | 4.5716 | |
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| 3.9485 | 22.58 | 700 | 4.3972 | |
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| 3.6496 | 25.81 | 800 | 4.2725 | |
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| 3.4384 | 29.03 | 900 | 4.1514 | |
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| 3.2557 | 32.26 | 1000 | 4.1532 | |
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| 3.0924 | 35.48 | 1100 | 3.9699 | |
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| 2.8789 | 38.71 | 1200 | 3.8153 | |
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| 2.7001 | 41.94 | 1300 | 3.8936 | |
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| 2.5654 | 45.16 | 1400 | 3.8185 | |
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| 2.4543 | 48.39 | 1500 | 3.9040 | |
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| 2.2817 | 51.61 | 1600 | 3.7283 | |
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| 2.2239 | 54.84 | 1700 | 3.6337 | |
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| 2.1119 | 58.06 | 1800 | 3.7746 | |
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| 1.9952 | 61.29 | 1900 | 3.5909 | |
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| 1.9466 | 64.52 | 2000 | 3.5679 | |
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| 1.8244 | 67.74 | 2100 | 3.6370 | |
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| 1.7837 | 70.97 | 2200 | 3.6295 | |
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| 1.6972 | 74.19 | 2300 | 3.6373 | |
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| 1.6845 | 77.42 | 2400 | 3.4213 | |
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| 1.6453 | 80.65 | 2500 | 3.5497 | |
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| 1.5759 | 83.87 | 2600 | 3.5886 | |
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| 1.5506 | 87.1 | 2700 | 3.4016 | |
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| 1.5294 | 90.32 | 2800 | 3.3665 | |
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| 1.4915 | 93.55 | 2900 | 3.3038 | |
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| 1.5035 | 96.77 | 3000 | 3.3139 | |
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| 1.4601 | 100.0 | 3100 | 3.5202 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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