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Model save

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  1. README.md +15 -15
README.md CHANGED
@@ -21,11 +21,11 @@ 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: 0.5555
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- - F1: 0.6007
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- - Accuracy: 0.696
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- - Precision: 0.6271
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- - Recall: 0.696
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  ## Model description
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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: 128
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- - eval_batch_size: 128
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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: cosine
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|:------:|
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- | No log | 0 | 0 | 0.8275 | 0.2749 | 0.336 | 0.5265 | 0.336 |
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- | No log | 1.0 | 8 | 0.6056 | 0.6355 | 0.669 | 0.6265 | 0.669 |
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- | 0.7136 | 2.0 | 16 | 0.5566 | 0.6004 | 0.693 | 0.6178 | 0.693 |
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- | 0.5579 | 3.0 | 24 | 0.5555 | 0.6007 | 0.696 | 0.6271 | 0.696 |
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  ### Framework versions
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  - Transformers 4.48.1
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- - Pytorch 2.5.1+cu124
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- - Datasets 3.2.0
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  - Tokenizers 0.21.0
 
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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: 0.3830
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+ - F1: 0.8183
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+ - Accuracy: 0.8212
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+ - Precision: 0.8171
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+ - Recall: 0.8212
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  ## Model description
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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: cosine
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|:---------:|:------:|
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+ | No log | 0 | 0 | 0.7214 | 0.5368 | 0.5168 | 0.6201 | 0.5168 |
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+ | 0.5801 | 1.0 | 6158 | 0.4019 | 0.8069 | 0.8092 | 0.8056 | 0.8092 |
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+ | 0.4354 | 2.0 | 12316 | 0.3835 | 0.8176 | 0.8212 | 0.8165 | 0.8212 |
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+ | 0.4089 | 3.0 | 18474 | 0.3830 | 0.8183 | 0.8212 | 0.8171 | 0.8212 |
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  ### Framework versions
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  - Transformers 4.48.1
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.0.1
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  - Tokenizers 0.21.0