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--- |
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license: apache-2.0 |
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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: google/flan-t5-large |
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model-index: |
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- name: LoRA-FlanT5-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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# LoRA-FlanT5-large |
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This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co./google/flan-t5-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0791 |
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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: 5e-05 |
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- train_batch_size: 3 |
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- eval_batch_size: 3 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 12 |
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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: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.9842 | 0.24 | 250 | 0.0915 | |
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| 0.1063 | 0.48 | 500 | 0.0848 | |
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| 0.1006 | 0.72 | 750 | 0.0823 | |
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| 0.0991 | 0.96 | 1000 | 0.0812 | |
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| 0.0979 | 1.2 | 1250 | 0.0805 | |
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| 0.0966 | 1.44 | 1500 | 0.0801 | |
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| 0.0946 | 1.69 | 1750 | 0.0798 | |
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| 0.0965 | 1.93 | 2000 | 0.0797 | |
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| 0.0964 | 2.17 | 2250 | 0.0795 | |
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| 0.0953 | 2.41 | 2500 | 0.0794 | |
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| 0.095 | 2.65 | 2750 | 0.0793 | |
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| 0.0958 | 2.89 | 3000 | 0.0792 | |
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| 0.0952 | 3.13 | 3250 | 0.0792 | |
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| 0.095 | 3.37 | 3500 | 0.0792 | |
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| 0.0966 | 3.61 | 3750 | 0.0792 | |
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| 0.0948 | 3.85 | 4000 | 0.0792 | |
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| 0.0954 | 4.09 | 4250 | 0.0791 | |
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| 0.0944 | 4.33 | 4500 | 0.0792 | |
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| 0.0947 | 4.57 | 4750 | 0.0791 | |
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| 0.0962 | 4.81 | 5000 | 0.0791 | |
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| 0.0947 | 5.06 | 5250 | 0.0792 | |
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| 0.0943 | 5.3 | 5500 | 0.0791 | |
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| 0.0946 | 5.54 | 5750 | 0.0792 | |
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| 0.0956 | 5.78 | 6000 | 0.0791 | |
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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 2.1.2 |
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- Datasets 2.19.1 |
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- Tokenizers 0.15.2 |
