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benitoals
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my-lora-hf-sum

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  1. .gitattributes +1 -0
  2. README.md +143 -0
  3. adapter_config.json +32 -0
  4. adapter_model.safetensors +3 -0
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  9. spiece.model +3 -0
  10. tokenizer.json +3 -0
  11. tokenizer_config.json +840 -0
  12. training_args.bin +3 -0
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README.md ADDED
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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/mt5-small
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: my-lora-hf-sum
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+ results: []
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+ ---
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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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+
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+ # my-lora-hf-sum
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+
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+ This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 8.8834
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+ - Rouge1: 0.7694
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+ - Rouge2: 0.2147
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+ - Rougel: 0.6887
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+ - Rougelsum: 0.7056
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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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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+ - num_epochs: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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+ |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
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+ | 26.8 | 0.0251 | 5 | 17.7235 | 0.4479 | 0.0229 | 0.4381 | 0.4408 |
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+ | 22.7614 | 0.0503 | 10 | 17.5699 | 0.5096 | 0.0229 | 0.4851 | 0.4837 |
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+ | 25.4291 | 0.0754 | 15 | 17.4004 | 0.4895 | 0.0229 | 0.4760 | 0.4770 |
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+ | 24.2329 | 0.1005 | 20 | 17.3355 | 0.4011 | 0.0229 | 0.4091 | 0.4097 |
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+ | 27.2941 | 0.1256 | 25 | 17.3291 | 0.3714 | 0.0229 | 0.3764 | 0.3806 |
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+ | 26.2486 | 0.1508 | 30 | 17.2167 | 0.3714 | 0.0229 | 0.3764 | 0.3806 |
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+ | 22.6219 | 0.1759 | 35 | 17.0234 | 0.3714 | 0.0229 | 0.3764 | 0.3806 |
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+ | 22.8832 | 0.2010 | 40 | 16.9310 | 0.3492 | 0.0229 | 0.3543 | 0.3580 |
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+ | 24.3708 | 0.2261 | 45 | 16.8126 | 0.3722 | 0.0229 | 0.3798 | 0.3821 |
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+ | 24.1446 | 0.2513 | 50 | 16.7162 | 0.3442 | 0.0229 | 0.3526 | 0.3520 |
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+ | 24.4794 | 0.2764 | 55 | 16.5429 | 0.3442 | 0.0229 | 0.3526 | 0.3520 |
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+ | 24.2086 | 0.3015 | 60 | 16.3896 | 0.3442 | 0.0229 | 0.3526 | 0.3520 |
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+ | 23.4245 | 0.3266 | 65 | 16.2550 | 0.3218 | 0.0229 | 0.3278 | 0.3254 |
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+ | 21.0837 | 0.3518 | 70 | 16.0502 | 0.3223 | 0.0229 | 0.3304 | 0.3275 |
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+ | 23.4064 | 0.3769 | 75 | 15.9576 | 0.3223 | 0.0229 | 0.3304 | 0.3275 |
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+ | 20.5418 | 0.4020 | 80 | 15.7345 | 0.3086 | 0.0229 | 0.3166 | 0.3160 |
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+ | 22.4424 | 0.4271 | 85 | 15.5302 | 0.2892 | 0.0229 | 0.2941 | 0.2983 |
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+ | 20.0642 | 0.4523 | 90 | 15.3498 | 0.3296 | 0.0493 | 0.3358 | 0.3386 |
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+ | 21.9881 | 0.4774 | 95 | 15.1718 | 0.3165 | 0.0493 | 0.3215 | 0.3253 |
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+ | 22.4813 | 0.5025 | 100 | 15.0168 | 0.3169 | 0.0493 | 0.3216 | 0.3257 |
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+ | 24.2963 | 0.5276 | 105 | 14.7464 | 0.3309 | 0.0493 | 0.3337 | 0.3370 |
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+ | 23.2294 | 0.5528 | 110 | 14.4756 | 0.3597 | 0.0493 | 0.3608 | 0.3642 |
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+ | 20.3992 | 0.5779 | 115 | 14.2512 | 0.3714 | 0.0493 | 0.3584 | 0.3635 |
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+ | 20.2597 | 0.6030 | 120 | 13.9527 | 0.3771 | 0.0493 | 0.3697 | 0.3743 |
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+ | 19.3918 | 0.7035 | 140 | 13.2160 | 0.3961 | 0.0852 | 0.3963 | 0.4077 |
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+ | 18.2876 | 0.7286 | 145 | 13.0702 | 0.3970 | 0.0852 | 0.3976 | 0.4095 |
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+ | 22.2212 | 0.7538 | 150 | 12.8667 | 0.3457 | 0.0852 | 0.3437 | 0.3524 |
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+ | 19.2252 | 0.7789 | 155 | 12.6627 | 0.3457 | 0.0852 | 0.3437 | 0.3524 |
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+ | 16.53 | 1.1055 | 220 | 10.3394 | 0.3811 | 0.0852 | 0.3752 | 0.3898 |
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+ | 13.9456 | 1.9849 | 395 | 8.8834 | 0.7694 | 0.2147 | 0.6887 | 0.7056 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.14.0
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+ - Transformers 4.49.0
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.3.2
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+ - Tokenizers 0.21.0
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