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README.md
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---
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library_name: peft
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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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model-index:
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- name: flan-t5-gen-retrieval-lora
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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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# flan-t5-gen-retrieval-lora
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This model is a fine-tuned version of [google-t5/t5-large](https://huggingface.co/google-t5/t5-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8377
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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: 4
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- eval_batch_size: 4
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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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- training_steps: 500
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.0087 | 0.0491 | 405 | 1.2918 |
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| 1.0558 | 0.0497 | 410 | 1.2060 |
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| 1.0558 | 0.0503 | 415 | 1.1487 |
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| 0.8712 | 0.0509 | 420 | 1.1032 |
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| 0.8712 | 0.0515 | 425 | 1.0525 |
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| 0.7341 | 0.0521 | 430 | 1.0037 |
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| 0.7341 | 0.0527 | 435 | 0.9570 |
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| 0.7253 | 0.0533 | 440 | 0.9061 |
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| 0.7253 | 0.0539 | 445 | 0.8771 |
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| 0.6724 | 0.0545 | 450 | 0.8519 |
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| 0.6724 | 0.0552 | 455 | 0.8448 |
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| 0.6172 | 0.0558 | 460 | 0.8431 |
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| 0.6172 | 0.0564 | 465 | 0.8414 |
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| 0.6013 | 0.0570 | 470 | 0.8399 |
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| 0.6013 | 0.0576 | 475 | 0.8391 |
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| 0.5868 | 0.0582 | 480 | 0.8385 |
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| 0.5868 | 0.0588 | 485 | 0.8383 |
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| 0.6088 | 0.0594 | 490 | 0.8380 |
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| 0.6088 | 0.06 | 495 | 0.8378 |
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| 0.6092 | 0.0606 | 500 | 0.8377 |
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### Framework versions
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- PEFT 0.14.0
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- Transformers 4.51.3
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- Pytorch 2.6.0+cu124
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- Datasets 3.6.0
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- Tokenizers 0.21.1
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