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--- |
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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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- precision |
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- recall |
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model-index: |
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- name: sentic-singletTextWcBerta-Fold1 |
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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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# sentic-singletTextWcBerta-Fold1 |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5627 |
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- Accuracy: 0.7510 |
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- Precision: 0.7401 |
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- Recall: 0.7510 |
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- F1 Score: 0.7431 |
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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: 1e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:| |
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| No log | 1.0 | 60 | 0.6901 | 0.7040 | 0.7917 | 0.7040 | 0.5827 | |
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| 0.501 | 2.0 | 120 | 0.5192 | 0.7354 | 0.7138 | 0.7354 | 0.6994 | |
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| 0.501 | 3.0 | 180 | 0.5411 | 0.7270 | 0.7045 | 0.7270 | 0.7048 | |
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| 0.4839 | 4.0 | 240 | 0.8009 | 0.7029 | 0.6429 | 0.7029 | 0.5822 | |
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| 0.4849 | 5.0 | 300 | 0.5294 | 0.7374 | 0.7163 | 0.7374 | 0.7066 | |
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| 0.4849 | 6.0 | 360 | 0.5430 | 0.7301 | 0.7109 | 0.7301 | 0.7132 | |
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| 0.4684 | 7.0 | 420 | 0.5570 | 0.7312 | 0.7104 | 0.7312 | 0.7110 | |
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| 0.4684 | 8.0 | 480 | 0.5740 | 0.7416 | 0.7258 | 0.7416 | 0.7006 | |
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| 0.4182 | 9.0 | 540 | 0.6109 | 0.7458 | 0.7328 | 0.7458 | 0.7054 | |
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| 0.4052 | 10.0 | 600 | 0.5607 | 0.7490 | 0.7357 | 0.7490 | 0.7383 | |
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| 0.4052 | 11.0 | 660 | 0.5974 | 0.7510 | 0.7369 | 0.7510 | 0.7182 | |
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| 0.3884 | 12.0 | 720 | 0.5715 | 0.7333 | 0.7423 | 0.7333 | 0.7370 | |
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| 0.3884 | 13.0 | 780 | 0.5603 | 0.7552 | 0.7463 | 0.7552 | 0.7492 | |
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| 0.364 | 14.0 | 840 | 0.5610 | 0.7573 | 0.7511 | 0.7573 | 0.7535 | |
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| 0.3564 | 15.0 | 900 | 0.5627 | 0.7510 | 0.7401 | 0.7510 | 0.7431 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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