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scbtm
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ModernBERT_wine_quality_reviews_ft

Text Classification
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modernbert
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End of training

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  1. README.md +42 -36
  2. model.safetensors +1 -1
  3. runs/Jan24_12-36-47_236db8c19ecc/events.out.tfevents.1737727152.236db8c19ecc.2035.1 +3 -0
README.md CHANGED
@@ -19,9 +19,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.68
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- - Accuracy: 0.70
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- - F1: 0.70
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  ## Model description
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@@ -40,47 +40,53 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 4e-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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - lr_scheduler_warmup_ratio: 0.1
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  - num_epochs: 5
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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- |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
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- | 1.1775 | 0.0826 | 350 | 0.9993 | 0.5336 | 0.5225 |
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- | 0.9496 | 0.1653 | 700 | 0.9632 | 0.5569 | 0.5411 |
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- | 0.8658 | 0.2479 | 1050 | 0.8257 | 0.6273 | 0.6272 |
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- | 0.8287 | 0.3306 | 1400 | 0.8655 | 0.5998 | 0.5742 |
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- | 0.8018 | 0.4132 | 1750 | 0.7638 | 0.6580 | 0.6510 |
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- | 0.7915 | 0.4959 | 2100 | 0.7481 | 0.6661 | 0.6662 |
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- | 0.767 | 0.5785 | 2450 | 0.7572 | 0.6626 | 0.6613 |
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- | 0.7525 | 0.6612 | 2800 | 0.7223 | 0.6747 | 0.6719 |
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- | 0.7498 | 0.7438 | 3150 | 0.7216 | 0.6768 | 0.6712 |
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- | 0.7258 | 0.8264 | 3500 | 0.7173 | 0.6762 | 0.6733 |
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- | 0.7183 | 0.9091 | 3850 | 0.7186 | 0.6786 | 0.6764 |
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- | 0.7251 | 0.9917 | 4200 | 0.7052 | 0.6822 | 0.6762 |
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- | 0.6534 | 1.0744 | 4550 | 0.7090 | 0.6860 | 0.6859 |
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- | 0.6425 | 1.1570 | 4900 | 0.7870 | 0.6512 | 0.6479 |
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- | 0.6321 | 1.2397 | 5250 | 0.6944 | 0.6899 | 0.6894 |
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- | 0.6283 | 1.3223 | 5600 | 0.7030 | 0.6869 | 0.6851 |
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- | 0.633 | 1.4050 | 5950 | 0.7000 | 0.6876 | 0.6859 |
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- | 0.6326 | 1.4876 | 6300 | 0.7044 | 0.6848 | 0.6823 |
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- | 0.6305 | 1.5702 | 6650 | 0.7002 | 0.6872 | 0.6832 |
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- | 0.6288 | 1.6529 | 7000 | 0.7076 | 0.6877 | 0.6856 |
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- | 0.625 | 1.7355 | 7350 | 0.6831 | 0.6930 | 0.6929 |
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- | 0.6394 | 1.8182 | 7700 | 0.6944 | 0.6859 | 0.6829 |
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- | 0.6221 | 1.9008 | 8050 | 0.6790 | 0.6966 | 0.6967 |
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- | 0.62 | 1.9835 | 8400 | 0.6928 | 0.6889 | 0.6896 |
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- | 0.4506 | 2.0661 | 8750 | 0.8053 | 0.6911 | 0.6896 |
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- | 0.3982 | 2.1488 | 9100 | 0.9036 | 0.6843 | 0.6839 |
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- | 0.3928 | 2.2314 | 9450 | 0.8230 | 0.6871 | 0.6873 |
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- | 0.3855 | 2.3140 | 9800 | 0.8589 | 0.6873 | 0.6864 |
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6671
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+ - Accuracy: 0.7019
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+ - F1: 0.7024
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  ## Model description
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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: 32
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  - eval_batch_size: 32
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  - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.8,0.8) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.15
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  - num_epochs: 5
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|
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+ | 1.1457 | 0.0826 | 350 | 0.9894 | 0.5461 | 0.5305 |
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+ | 0.9441 | 0.1653 | 700 | 1.1213 | 0.4977 | 0.4827 |
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+ | 0.8589 | 0.2479 | 1050 | 0.8232 | 0.6297 | 0.6277 |
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+ | 0.8131 | 0.3306 | 1400 | 0.8268 | 0.6177 | 0.5956 |
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+ | 0.7837 | 0.4132 | 1750 | 0.7474 | 0.6679 | 0.6663 |
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+ | 0.7726 | 0.4959 | 2100 | 0.8008 | 0.6397 | 0.6269 |
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+ | 0.7576 | 0.5785 | 2450 | 0.7571 | 0.6533 | 0.6550 |
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+ | 0.7528 | 0.6612 | 2800 | 0.7414 | 0.6666 | 0.6598 |
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+ | 0.7588 | 0.7438 | 3150 | 0.7627 | 0.6588 | 0.6397 |
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+ | 0.7416 | 0.8264 | 3500 | 0.7259 | 0.6736 | 0.6739 |
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+ | 0.7303 | 0.9091 | 3850 | 0.7052 | 0.6847 | 0.6812 |
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+ | 0.7313 | 0.9917 | 4200 | 0.7059 | 0.6860 | 0.6799 |
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+ | 0.6647 | 1.0744 | 4550 | 0.7002 | 0.6890 | 0.6887 |
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+ | 0.6606 | 1.1570 | 4900 | 0.7712 | 0.6583 | 0.6502 |
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+ | 0.65 | 1.2397 | 5250 | 0.6868 | 0.6917 | 0.6904 |
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+ | 0.6464 | 1.3223 | 5600 | 0.7371 | 0.6757 | 0.6673 |
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+ | 0.6494 | 1.4050 | 5950 | 0.7323 | 0.6751 | 0.6724 |
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+ | 0.6505 | 1.4876 | 6300 | 0.6952 | 0.6877 | 0.6856 |
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+ | 0.6499 | 1.5702 | 6650 | 0.6935 | 0.6893 | 0.6812 |
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+ | 0.6399 | 1.6529 | 7000 | 0.7099 | 0.6873 | 0.6826 |
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+ | 0.632 | 1.7355 | 7350 | 0.6912 | 0.6942 | 0.6915 |
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+ | 0.6488 | 1.8182 | 7700 | 0.6741 | 0.6971 | 0.6972 |
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+ | 0.6331 | 1.9008 | 8050 | 0.6881 | 0.6933 | 0.6932 |
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+ | 0.6339 | 1.9835 | 8400 | 0.6671 | 0.7019 | 0.7024 |
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+ | 0.4914 | 2.0661 | 8750 | 0.7598 | 0.6989 | 0.6982 |
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+ | 0.4498 | 2.1488 | 9100 | 0.7617 | 0.6997 | 0.6996 |
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+ | 0.4407 | 2.2314 | 9450 | 0.7674 | 0.6950 | 0.6945 |
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+ | 0.4468 | 2.3140 | 9800 | 0.7978 | 0.6946 | 0.6932 |
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+ | 0.4486 | 2.3967 | 10150 | 0.7718 | 0.6929 | 0.6926 |
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+ | 0.4462 | 2.4793 | 10500 | 0.7928 | 0.6808 | 0.6811 |
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+ | 0.4483 | 2.5620 | 10850 | 0.7678 | 0.6957 | 0.6966 |
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+ | 0.4347 | 2.6446 | 11200 | 0.7687 | 0.6935 | 0.6938 |
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+ | 0.4429 | 2.7273 | 11550 | 0.7496 | 0.6969 | 0.6973 |
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+ | 0.4415 | 2.8099 | 11900 | 0.7621 | 0.6968 | 0.6963 |
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  ### Framework versions
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runs/Jan24_12-36-47_236db8c19ecc/events.out.tfevents.1737727152.236db8c19ecc.2035.1 ADDED
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