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featured-articles

Text Classification
Transformers
TensorBoard
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
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End of training

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Files changed (7) hide show
  1. README.md +19 -11
  2. model.safetensors +1 -1
  3. runs/May29_12-36-49_MacBook-Pro-2.local/events.out.tfevents.1748540209.MacBook-Pro-2.local.97121.0 +3 -0
  4. runs/May29_12-37-56_MacBook-Pro-2.local/events.out.tfevents.1748540276.MacBook-Pro-2.local.97336.0 +3 -0
  5. tokenizer.json +2 -2
  6. tokenizer_config.json +1 -1
  7. training_args.bin +1 -1
README.md CHANGED
@@ -5,7 +5,7 @@ base_model: answerdotai/ModernBERT-base
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  tags:
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  - generated_from_trainer
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  metrics:
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- - f1
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  model-index:
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  - name: featured-articles
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  results: []
@@ -18,8 +18,15 @@ 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: 0.8059
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- - F1: 0.6817
 
 
 
 
 
 
 
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  ## Model description
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@@ -38,21 +45,22 @@ 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: 5e-05
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  - train_batch_size: 8
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- - eval_batch_size: 4
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  - seed: 42
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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: linear
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- - num_epochs: 3
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.6394 | 1.0 | 269 | 0.5860 | 0.6517 |
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- | 0.4479 | 2.0 | 538 | 0.7460 | 0.5421 |
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- | 0.2307 | 3.0 | 807 | 0.8059 | 0.6817 |
 
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  ### Framework versions
 
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  tags:
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  - generated_from_trainer
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  metrics:
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+ - accuracy
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  model-index:
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  - name: featured-articles
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  results: []
 
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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: 1.9620
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+ - Weighted F1: 0.6740
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+ - Accepted Precision: 0.7453
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+ - Accepted Recall: 0.7790
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+ - Accepted F1: 0.7618
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+ - Rejected Precision: 0.5273
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+ - Rejected Recall: 0.4807
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+ - Rejected F1: 0.5029
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+ - Accuracy: 0.6779
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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: 3e-05
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  - train_batch_size: 8
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+ - eval_batch_size: 8
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  - seed: 42
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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: linear
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+ - num_epochs: 4
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Weighted F1 | Accepted Precision | Accepted Recall | Accepted F1 | Rejected Precision | Rejected Recall | Rejected F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----------:|:------------------:|:---------------:|:-----------:|:------------------:|:---------------:|:-----------:|:--------:|
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+ | 0.6595 | 1.0 | 267 | 0.6187 | 0.6876 | 0.752 | 0.7989 | 0.7747 | 0.5535 | 0.4862 | 0.5176 | 0.6929 |
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+ | 0.4807 | 2.0 | 534 | 0.7625 | 0.5677 | 0.8030 | 0.4504 | 0.5771 | 0.4226 | 0.7845 | 0.5493 | 0.5637 |
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+ | 0.3013 | 3.0 | 801 | 1.7444 | 0.6577 | 0.7105 | 0.9178 | 0.8010 | 0.6282 | 0.2707 | 0.3784 | 0.6985 |
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+ | 0.0381 | 4.0 | 1068 | 1.9620 | 0.6740 | 0.7453 | 0.7790 | 0.7618 | 0.5273 | 0.4807 | 0.5029 | 0.6779 |
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  ### Framework versions
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tokenizer.json CHANGED
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tokenizer_config.json CHANGED
@@ -937,7 +937,7 @@
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