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--- |
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license: apache-2.0 |
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base_model: google-t5/t5-large |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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model-index: |
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- name: adversarial_qa_dbert_based_on |
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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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# adversarial_qa_dbert_based_on |
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This model is a fine-tuned version of [google-t5/t5-large](https://huggingface.co/google-t5/t5-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1381 |
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- Exact Match: 0.3467 |
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- Bleu: 0.3083 |
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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: 0.0002 |
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- train_batch_size: 2 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- total_train_batch_size: 8 |
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- total_eval_batch_size: 64 |
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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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- num_epochs: 5.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Exact Match | Bleu | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------:|:------:| |
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| 1.0162 | 1.0 | 63 | 0.7607 | 0.2754 | 0.2749 | |
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| 0.3929 | 2.0 | 126 | 0.7943 | 0.2959 | 0.2412 | |
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| 0.1542 | 3.0 | 189 | 1.0053 | 0.3018 | 0.2720 | |
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| 0.0544 | 4.0 | 252 | 1.1005 | 0.3457 | 0.3185 | |
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| 0.0239 | 5.0 | 315 | 1.1381 | 0.3467 | 0.3083 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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