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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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model-index: |
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- name: Sentiment-Analysis-Model |
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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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# Sentiment-Analysis-Model |
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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: 0.7057 |
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- F1 Score: 0.6844 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Score | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 0.8268 | 0.5 | 500 | 0.7473 | 0.6734 | |
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| 0.792 | 1.0 | 1000 | 0.7927 | 0.6723 | |
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| 0.7531 | 1.5 | 1500 | 0.7387 | 0.6705 | |
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| 0.7527 | 2.0 | 2000 | 0.7057 | 0.6844 | |
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| 0.7302 | 2.5 | 2500 | 0.7520 | 0.6775 | |
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| 0.7355 | 3.0 | 3000 | 0.7379 | 0.6797 | |
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| 0.7245 | 3.5 | 3500 | 0.7260 | 0.6811 | |
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| 0.7383 | 4.0 | 4000 | 0.7445 | 0.6791 | |
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| 0.7271 | 4.5 | 4500 | 0.7372 | 0.6787 | |
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| 0.7306 | 5.0 | 5000 | 0.7308 | 0.6816 | |
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| 0.7259 | 5.5 | 5500 | 0.7407 | 0.6851 | |
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| 0.7286 | 6.0 | 6000 | 0.7517 | 0.6854 | |
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| 0.7515 | 6.5 | 6500 | 0.7702 | 0.6822 | |
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| 0.6996 | 7.0 | 7000 | 0.7286 | 0.6877 | |
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| 0.7067 | 7.5 | 7500 | 0.7413 | 0.6832 | |
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| 0.7195 | 8.0 | 8000 | 0.7561 | 0.6842 | |
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| 0.7041 | 8.5 | 8500 | 0.7812 | 0.6819 | |
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| 0.7329 | 9.0 | 9000 | 0.7717 | 0.6846 | |
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| 0.7046 | 9.5 | 9500 | 0.7625 | 0.6817 | |
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| 0.722 | 10.0 | 10000 | 0.7432 | 0.6897 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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