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roberta-base-squad2-finetuned-BioASQ-ds

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  1. README.md +9 -11
  2. model.safetensors +1 -1
  3. runs/Apr10_22-46-22_4357093ed208/events.out.tfevents.1712789183.4357093ed208.3659.0 +2 -2
  4. runs/Apr10_22-46-22_4357093ed208/events.out.tfevents.1712793517.4357093ed208.3659.1 +3 -0
README.md CHANGED
@@ -1,9 +1,8 @@
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  ---
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  license: cc-by-4.0
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- library_name: peft
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  tags:
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  - generated_from_trainer
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- base_model: deepset/roberta-base-squad2
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  model-index:
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  - name: roberta-base-squad2-finetuned-BioASQ-ds
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  results: []
@@ -16,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5794
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  ## Model description
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@@ -36,8 +35,8 @@ More information needed
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
@@ -47,16 +46,15 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 2.1583 | 1.0 | 778 | 1.7934 |
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- | 1.7158 | 2.0 | 1556 | 1.6634 |
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- | 1.6443 | 3.0 | 2334 | 1.5985 |
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- | 1.5896 | 4.0 | 3112 | 1.5794 |
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  ### Framework versions
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- - PEFT 0.10.0
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  - Transformers 4.39.3
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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- - Tokenizers 0.15.2
 
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  ---
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  license: cc-by-4.0
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+ base_model: deepset/roberta-base-squad2
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  tags:
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  - generated_from_trainer
 
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  model-index:
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  - name: roberta-base-squad2-finetuned-BioASQ-ds
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  results: []
 
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  This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8373
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  ## Model description
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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: 8
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+ - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.0159 | 1.0 | 1556 | 0.9558 |
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+ | 0.7883 | 2.0 | 3112 | 0.8757 |
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+ | 0.7006 | 3.0 | 4668 | 0.8293 |
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+ | 0.6117 | 4.0 | 6224 | 0.8373 |
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  ### Framework versions
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  - Transformers 4.39.3
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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