End of training
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README.md
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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.
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- Accuracy: 0.
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## Model description
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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:
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- total_train_batch_size:
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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:
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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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| 1.774 | 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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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: 0.7135
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- Accuracy: 0.6114
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## Model description
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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: 10
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- total_train_batch_size: 60
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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: 100
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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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| 6.6012 | 0.2994 | 20 | 0.6613 | 0.6114 |
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| 5.841 | 0.5988 | 40 | 0.7060 | 0.6114 |
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| 7.3284 | 0.8982 | 60 | 0.6671 | 0.6114 |
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| 6.9088 | 1.2096 | 80 | 0.6861 | 0.4834 |
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| 7.1679 | 1.5090 | 100 | 0.7135 | 0.6114 |
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### Framework versions
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model.safetensors
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