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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: safetune |
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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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# safetune |
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This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1197 |
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- Mse: 1.1197 |
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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: 8 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mse | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 2.2203 | 0.05 | 50 | 1.8289 | 1.8289 | |
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| 1.8997 | 0.1 | 100 | 1.7516 | 1.7516 | |
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| 1.4082 | 0.15 | 150 | 1.3950 | 1.3950 | |
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| 1.5899 | 0.2 | 200 | 1.9590 | 1.9590 | |
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| 1.3633 | 0.25 | 250 | 1.3316 | 1.3316 | |
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| 1.3758 | 0.29 | 300 | 1.2860 | 1.2860 | |
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| 1.3339 | 0.34 | 350 | 1.2694 | 1.2694 | |
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| 1.2831 | 0.39 | 400 | 1.3048 | 1.3048 | |
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| 1.2928 | 0.44 | 450 | 1.2395 | 1.2395 | |
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| 1.2506 | 0.49 | 500 | 1.4315 | 1.4315 | |
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| 1.204 | 0.54 | 550 | 1.1596 | 1.1596 | |
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| 1.1749 | 0.59 | 600 | 1.1995 | 1.1995 | |
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| 1.134 | 0.64 | 650 | 1.3782 | 1.3782 | |
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| 1.3097 | 0.69 | 700 | 1.1867 | 1.1867 | |
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| 1.29 | 0.74 | 750 | 1.2024 | 1.2024 | |
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| 1.1575 | 0.78 | 800 | 1.1197 | 1.1197 | |
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| 1.2148 | 0.83 | 850 | 1.1944 | 1.1944 | |
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| 1.1597 | 0.88 | 900 | 1.2023 | 1.2023 | |
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| 1.1422 | 0.93 | 950 | 1.1546 | 1.1546 | |
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| 1.0734 | 0.98 | 1000 | 1.2593 | 1.2593 | |
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### Framework versions |
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- Transformers 4.30.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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