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--- |
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license: mit |
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base_model: roberta-large |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: roberta-large |
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results: [] |
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library_name: peft |
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datasets: |
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- AndersGiovanni/10-dim |
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language: |
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- en |
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pipeline_tag: text-classification |
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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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# roberta-large |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2277 |
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- Accuracy: 0.0883 |
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- Precision: 0.6211 |
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- Recall: 0.1909 |
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- F1: 0.2920 |
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- Hamming Loss: 0.1984 |
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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: 0.0001 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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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: constant |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 10 |
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### Training results |
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### Framework versions |
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- PEFT 0.5.0 |
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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 |
