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--- |
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library_name: transformers |
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license: mit |
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base_model: deepset/gbert-large |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: flausch_span_gbert-large |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# flausch_span_gbert-large |
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This model is a fine-tuned version of [deepset/gbert-large](https://huggingface.co/deepset/gbert-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6725 |
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- Model Preparation Time: 0.0057 |
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- Precision: 0.5075 |
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- Recall: 0.6548 |
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- F1: 0.5718 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:---------:|:------:|:------:| |
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| 0.5882 | 1.0 | 517 | 0.5842 | 0.0057 | 0.4539 | 0.6280 | 0.5270 | |
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| 0.3879 | 2.0 | 1034 | 0.5720 | 0.0057 | 0.5194 | 0.6646 | 0.5831 | |
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| 0.256 | 3.0 | 1551 | 0.6075 | 0.0057 | 0.4985 | 0.6445 | 0.5622 | |
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| 0.1477 | 4.0 | 2068 | 0.6725 | 0.0057 | 0.5075 | 0.6548 | 0.5718 | |
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### Framework versions |
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- Transformers 4.52.2 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 2.14.4 |
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- Tokenizers 0.21.1 |
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