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--- |
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license: mit |
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base_model: roberta-base |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: fintunned-v2-roberta_GA |
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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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# fintunned-v2-roberta_GA |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1635 |
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- Accuracy: 0.9523 |
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- F1: 0.9527 |
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- Precision: 0.9534 |
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- Recall: 0.9523 |
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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: 16 |
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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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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 2.3896 | 0.45 | 50 | 2.2632 | 0.325 | 0.2696 | 0.4504 | 0.3447 | |
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| 1.2481 | 0.91 | 100 | 0.4536 | 0.8841 | 0.8873 | 0.8940 | 0.8892 | |
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| 0.3487 | 1.36 | 150 | 0.2978 | 0.9136 | 0.9161 | 0.9186 | 0.9167 | |
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| 0.2618 | 1.82 | 200 | 0.2472 | 0.9295 | 0.9319 | 0.9362 | 0.9313 | |
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| 0.2223 | 2.27 | 250 | 0.1872 | 0.9409 | 0.9415 | 0.9445 | 0.9408 | |
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| 0.076 | 2.73 | 300 | 0.1635 | 0.9523 | 0.9527 | 0.9534 | 0.9523 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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