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ModernBERT-large-classifier

Text Classification
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Safetensors
modernbert
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End of training

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  1. README.md +12 -11
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
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-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2639
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- - Accuracy: 0.8977
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- - F1: 0.8192
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  ## Model description
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@@ -46,17 +46,18 @@ The following hyperparameters were used during training:
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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: 2
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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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- | No log | 0 | 0 | 0.6260 | 0.6323 | 0.3557 |
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- | No log | 0.4026 | 126 | 0.3459 | 0.8489 | 0.7483 |
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- | No log | 0.8051 | 252 | 0.2980 | 0.8761 | 0.7868 |
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- | No log | 1.2077 | 378 | 0.2821 | 0.8825 | 0.7728 |
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- | 0.2826 | 1.6102 | 504 | 0.2739 | 0.8905 | 0.8006 |
 
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6461
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+ - Accuracy: 0.9033
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+ - F1: 0.8259
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  ## Model description
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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: 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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+ | No log | 0 | 0 | 0.8842 | 0.3485 | 0.3608 |
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+ | No log | 1.0 | 313 | 0.3089 | 0.8721 | 0.7360 |
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+ | 0.3005 | 2.0 | 626 | 0.2675 | 0.8929 | 0.8047 |
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+ | 0.3005 | 3.0 | 939 | 0.4474 | 0.8953 | 0.8251 |
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+ | 0.1032 | 4.0 | 1252 | 0.5724 | 0.9001 | 0.8237 |
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+ | 0.0322 | 5.0 | 1565 | 0.6461 | 0.9033 | 0.8259 |
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  ### Framework versions
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