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staghado
/
edu-modernbert

Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
Inference Endpoints
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Training in progress, step 27000

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  1. README.md +16 -16
  2. final/model.safetensors +1 -1
  3. final/tokenizer.json +1 -6
  4. final/training_args.bin +1 -1
  5. model.safetensors +1 -1
  6. tokenizer.json +1 -6
  7. training_args.bin +1 -1
README.md CHANGED
@@ -21,14 +21,14 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2860
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  - Precision: 0.5389
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- - Recall: 0.3948
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- - F1: 0.4306
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- - Accuracy: 0.6824
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- - Binary Precision: 0.7543
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- - Binary Recall: 0.4522
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- - Binary F1: 0.5654
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  - Binary Accuracy: 0.9373
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  ## Model description
@@ -60,15 +60,15 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Binary Precision | Binary Recall | Binary F1 | Binary Accuracy |
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  |:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:----------------:|:-------------:|:---------:|:---------------:|
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- | No log | 0 | 0 | 3.2225 | 0.1006 | 0.1672 | 0.0384 | 0.1250 | 0.0 | 0.0 | 0.0 | 0.9098 |
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- | 0.3184 | 2.4331 | 1000 | 0.3097 | 0.5223 | 0.3701 | 0.3955 | 0.6607 | 0.7759 | 0.3442 | 0.4769 | 0.9319 |
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- | 0.3056 | 4.8662 | 2000 | 0.3007 | 0.5272 | 0.3835 | 0.4127 | 0.6692 | 0.7653 | 0.3791 | 0.5071 | 0.9335 |
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- | 0.3019 | 7.2993 | 3000 | 0.3016 | 0.5252 | 0.3825 | 0.4131 | 0.6719 | 0.7829 | 0.3730 | 0.5052 | 0.9341 |
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- | 0.2981 | 9.7324 | 4000 | 0.2926 | 0.5413 | 0.3875 | 0.4207 | 0.6754 | 0.7487 | 0.4361 | 0.5511 | 0.9359 |
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- | 0.2952 | 12.1655 | 5000 | 0.2890 | 0.5352 | 0.3971 | 0.4317 | 0.6797 | 0.7439 | 0.4541 | 0.5639 | 0.9367 |
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- | 0.2936 | 14.5985 | 6000 | 0.2891 | 0.5332 | 0.3938 | 0.4288 | 0.6825 | 0.7705 | 0.4254 | 0.5482 | 0.9368 |
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- | 0.2856 | 17.0316 | 7000 | 0.2869 | 0.5434 | 0.3871 | 0.4237 | 0.6838 | 0.7689 | 0.4216 | 0.5446 | 0.9364 |
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- | 0.2888 | 19.4647 | 8000 | 0.2860 | 0.5389 | 0.3948 | 0.4306 | 0.6824 | 0.7543 | 0.4522 | 0.5654 | 0.9373 |
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2864
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  - Precision: 0.5389
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+ - Recall: 0.3949
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+ - F1: 0.4305
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+ - Accuracy: 0.6820
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+ - Binary Precision: 0.7559
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+ - Binary Recall: 0.4496
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+ - Binary F1: 0.5638
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  - Binary Accuracy: 0.9373
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  ## Model description
 
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Binary Precision | Binary Recall | Binary F1 | Binary Accuracy |
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  |:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:----------------:|:-------------:|:---------:|:---------------:|
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+ | No log | 0 | 0 | 2.4591 | 0.1116 | 0.1645 | 0.0484 | 0.1386 | 0.0 | 0.0 | 0.0 | 0.9098 |
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+ | 0.3196 | 2.4331 | 1000 | 0.3097 | 0.5201 | 0.3691 | 0.3946 | 0.6587 | 0.7614 | 0.3580 | 0.4870 | 0.9320 |
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+ | 0.3064 | 4.8662 | 2000 | 0.3067 | 0.5273 | 0.3882 | 0.4154 | 0.6599 | 0.7391 | 0.4375 | 0.5496 | 0.9353 |
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+ | 0.3088 | 7.2993 | 3000 | 0.2951 | 0.5353 | 0.3833 | 0.4169 | 0.6744 | 0.7656 | 0.4007 | 0.5261 | 0.9349 |
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+ | 0.2991 | 9.7324 | 4000 | 0.2975 | 0.5421 | 0.3921 | 0.4234 | 0.6699 | 0.7316 | 0.4643 | 0.5681 | 0.9363 |
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+ | 0.2957 | 12.1655 | 5000 | 0.2920 | 0.5362 | 0.3859 | 0.4207 | 0.6813 | 0.7811 | 0.3953 | 0.5249 | 0.9355 |
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+ | 0.2932 | 14.5985 | 6000 | 0.2881 | 0.5364 | 0.3946 | 0.4298 | 0.6824 | 0.7591 | 0.4351 | 0.5532 | 0.9366 |
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+ | 0.2862 | 17.0316 | 7000 | 0.2876 | 0.5411 | 0.3850 | 0.4213 | 0.6829 | 0.7713 | 0.4104 | 0.5358 | 0.9359 |
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+ | 0.2894 | 19.4647 | 8000 | 0.2864 | 0.5389 | 0.3949 | 0.4305 | 0.6820 | 0.7559 | 0.4496 | 0.5638 | 0.9373 |
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  ### Framework versions
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