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CoCoRooXin
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finetuned_robert

Text Classification
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roberta
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  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # finetuned_robert
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- This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the Topic-keyword inclusion dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3167
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- - F1: 0.8784
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- - Precision: 0.8025
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- - Recall: 0.9701
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- - Accuracy: 0.88
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  ## Model description
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@@ -44,26 +44,38 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
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- | 0.6992 | 0.56 | 10 | 0.6734 | 0.4536 | 0.7333 | 0.3284 | 0.6467 |
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- | 0.6606 | 1.11 | 20 | 0.5941 | 0.75 | 0.7391 | 0.7612 | 0.7733 |
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- | 0.5601 | 1.67 | 30 | 0.4531 | 0.8429 | 0.8082 | 0.8806 | 0.8533 |
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- | 0.4625 | 2.22 | 40 | 0.6246 | 0.7429 | 0.6019 | 0.9701 | 0.7 |
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- | 0.4354 | 2.78 | 50 | 0.4126 | 0.8280 | 0.7222 | 0.9701 | 0.82 |
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- | 0.3236 | 3.33 | 60 | 0.3631 | 0.8533 | 0.7711 | 0.9552 | 0.8533 |
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- | 0.2726 | 3.89 | 70 | 0.3337 | 0.8591 | 0.7805 | 0.9552 | 0.86 |
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- | 0.248 | 4.44 | 80 | 0.3383 | 0.8667 | 0.7831 | 0.9701 | 0.8667 |
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- | 0.2292 | 5.0 | 90 | 0.3167 | 0.8784 | 0.8025 | 0.9701 | 0.88 |
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  # finetuned_robert
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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: 0.2694
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+ - F1: 0.9041
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+ - Precision: 0.8354
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+ - Recall: 0.9851
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+ - Accuracy: 0.9067
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 32
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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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+ - num_epochs: 6
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
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+ | 0.7067 | 0.28 | 10 | 0.6843 | 0.0 | 0.0 | 0.0 | 0.5533 |
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+ | 0.7087 | 0.56 | 20 | 0.6786 | 0.0 | 0.0 | 0.0 | 0.5533 |
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+ | 0.6887 | 0.83 | 30 | 0.6543 | 0.7241 | 0.8571 | 0.6269 | 0.7867 |
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+ | 0.6773 | 1.11 | 40 | 0.6069 | 0.816 | 0.8793 | 0.7612 | 0.8467 |
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+ | 0.6073 | 1.39 | 50 | 0.4951 | 0.7711 | 0.6465 | 0.9552 | 0.7467 |
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+ | 0.5731 | 1.67 | 60 | 0.3976 | 0.8219 | 0.7595 | 0.8955 | 0.8267 |
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+ | 0.4806 | 1.94 | 70 | 0.3487 | 0.8421 | 0.8485 | 0.8358 | 0.86 |
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+ | 0.4685 | 2.22 | 80 | 0.5218 | 0.7811 | 0.6471 | 0.9851 | 0.7533 |
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+ | 0.4243 | 2.5 | 90 | 0.8471 | 0.7322 | 0.5776 | 1.0 | 0.6733 |
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+ | 0.3692 | 2.78 | 100 | 0.3453 | 0.8514 | 0.7778 | 0.9403 | 0.8533 |
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+ | 0.4633 | 3.06 | 110 | 0.2813 | 0.8611 | 0.8052 | 0.9254 | 0.8667 |
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+ | 0.3334 | 3.33 | 120 | 0.3090 | 0.8514 | 0.7778 | 0.9403 | 0.8533 |
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+ | 0.3167 | 3.61 | 130 | 0.3531 | 0.8497 | 0.7558 | 0.9701 | 0.8467 |
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+ | 0.2615 | 3.89 | 140 | 0.2679 | 0.8873 | 0.84 | 0.9403 | 0.8933 |
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+ | 0.2672 | 4.17 | 150 | 0.2528 | 0.8889 | 0.8312 | 0.9552 | 0.8933 |
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+ | 0.2103 | 4.44 | 160 | 0.2905 | 0.8649 | 0.7901 | 0.9552 | 0.8667 |
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+ | 0.2208 | 4.72 | 170 | 0.2992 | 0.8649 | 0.7901 | 0.9552 | 0.8667 |
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+ | 0.2267 | 5.0 | 180 | 0.2911 | 0.8859 | 0.8049 | 0.9851 | 0.8867 |
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+ | 0.1623 | 5.28 | 190 | 0.2355 | 0.9014 | 0.8533 | 0.9552 | 0.9067 |
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+ | 0.2148 | 5.56 | 200 | 0.2200 | 0.9091 | 0.8553 | 0.9701 | 0.9133 |
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+ | 0.1537 | 5.83 | 210 | 0.2694 | 0.9041 | 0.8354 | 0.9851 | 0.9067 |
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  ### Framework versions
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