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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 +17 -13
  2. model.safetensors +1 -1
  3. runs/May18_18-01-17_14d9f458975d/events.out.tfevents.1747591281.14d9f458975d.1682.0 +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: 0.4925
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- - Accuracy: 0.8698
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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: 4
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  - eval_batch_size: 1
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  - seed: 42
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- - gradient_accumulation_steps: 3
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  - total_train_batch_size: 12
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: constant
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- - num_epochs: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 1.3307 | 0.2757 | 50 | 0.8133 | 0.5547 |
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- | 2.4211 | 0.5515 | 100 | 0.6010 | 0.6615 |
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- | 1.9701 | 0.8272 | 150 | 0.5964 | 0.6901 |
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- | 0.2215 | 1.0993 | 200 | 0.6405 | 0.7109 |
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- | 0.1582 | 1.375 | 250 | 0.4628 | 0.7995 |
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- | 0.1519 | 1.6507 | 300 | 0.4207 | 0.7995 |
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- | 0.8939 | 1.9265 | 350 | 0.4925 | 0.8698 |
 
 
 
 
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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: 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
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+ - gradient_accumulation_steps: 2
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  - total_train_batch_size: 12
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: constant
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+ - training_steps: 550
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  ### Training results
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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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