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--- |
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license: apache-2.0 |
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base_model: distilbert/distilbert-base-multilingual-cased |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: distilbert-base-multilingual-cased_regression_finetuned_mobile01_all |
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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-multilingual-cased_regression_finetuned_mobile01_all |
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This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8877 |
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- Mse: 0.8877 |
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- Mae: 0.5973 |
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- Rmse: 0.9422 |
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- Mape: inf |
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- R Squared: 0.5145 |
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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: 3e-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: cosine |
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- lr_scheduler_warmup_steps: 778 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | Rmse | Mape | R Squared | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:----:|:---------:| |
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| 1.0906 | 1.0 | 7789 | 1.0449 | 1.0449 | 0.7032 | 1.0222 | inf | 0.4285 | |
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| 0.9156 | 2.0 | 15578 | 0.9369 | 0.9369 | 0.6340 | 0.9679 | inf | 0.4875 | |
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| 0.6858 | 3.0 | 23367 | 0.9153 | 0.9153 | 0.6189 | 0.9567 | inf | 0.4993 | |
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| 1.0272 | 4.0 | 31156 | 0.8877 | 0.8877 | 0.5973 | 0.9422 | inf | 0.5145 | |
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| 0.7273 | 5.0 | 38945 | 0.8928 | 0.8928 | 0.6004 | 0.9449 | inf | 0.5117 | |
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| 0.8211 | 6.0 | 46734 | 0.8880 | 0.8880 | 0.5936 | 0.9423 | inf | 0.5143 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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