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underscore2
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modernbert_agree_classifier

Text Classification
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modernbert
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End of training

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  1. README.md +14 -14
  2. model.safetensors +1 -1
  3. runs/May21_21-02-45_46d9a0ca97b3/events.out.tfevents.1747861369.46d9a0ca97b3.758.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.2279
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- - Accuracy: 0.7059
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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: 0.00016
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  - train_batch_size: 6
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  - eval_batch_size: 1
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  - seed: 42
@@ -52,17 +52,17 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 2.1915 | 0.2762 | 50 | 1.1417 | 0.2588 |
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- | 1.3494 | 0.5525 | 100 | 0.6381 | 0.7412 |
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- | 1.3588 | 0.8287 | 150 | 0.6750 | 0.5922 |
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- | 1.0859 | 1.1050 | 200 | 0.8046 | 0.7373 |
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- | 1.5857 | 1.3812 | 250 | 0.6222 | 0.6667 |
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- | 0.5529 | 1.6575 | 300 | 1.0381 | 0.4471 |
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- | 1.2417 | 1.9337 | 350 | 0.9943 | 0.6980 |
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- | 0.0183 | 2.2099 | 400 | 2.7391 | 0.6941 |
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- | 0.0112 | 2.4862 | 450 | 2.3648 | 0.6706 |
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- | 0.0004 | 2.7624 | 500 | 2.3759 | 0.6667 |
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- | 0.0007 | 3.0387 | 550 | 3.2279 | 0.7059 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7424
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+ - Accuracy: 0.5687
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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: 6.000000000000001e-05
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  - train_batch_size: 6
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  - eval_batch_size: 1
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 1.327 | 0.1497 | 50 | 0.6950 | 0.5640 |
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+ | 1.5088 | 0.2994 | 100 | 0.6833 | 0.5687 |
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+ | 1.2018 | 0.4491 | 150 | 0.6867 | 0.5687 |
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+ | 1.3053 | 0.5988 | 200 | 0.6923 | 0.5687 |
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+ | 1.2024 | 0.7485 | 250 | 0.6879 | 0.5687 |
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+ | 1.774 | 0.8982 | 300 | 0.7197 | 0.4313 |
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+ | 1.4274 | 1.0479 | 350 | 0.6862 | 0.5687 |
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+ | 1.199 | 1.1976 | 400 | 0.6995 | 0.5687 |
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+ | 1.4548 | 1.3473 | 450 | 0.7085 | 0.4313 |
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+ | 1.581 | 1.4970 | 500 | 0.6845 | 0.5687 |
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+ | 1.8775 | 1.6467 | 550 | 0.7424 | 0.5687 |
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  ### Framework versions
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