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--- |
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license: apache-2.0 |
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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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model-index: |
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- name: distilbert-base-uncased-finetuned-ft1500_norm500_aug5 |
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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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# distilbert-base-uncased-finetuned-ft1500_norm500_aug5 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8927 |
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- Mse: 2.9755 |
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- Mae: 1.0176 |
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- R2: 0.4184 |
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- Accuracy: 0.5003 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:--------:| |
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| 0.4176 | 1.0 | 3952 | 1.0499 | 3.4996 | 1.0853 | 0.3160 | 0.4593 | |
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| 0.3196 | 2.0 | 7904 | 0.8670 | 2.8901 | 1.0503 | 0.4351 | 0.4600 | |
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| 0.2084 | 3.0 | 11856 | 0.8927 | 2.9755 | 1.0176 | 0.4184 | 0.5003 | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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