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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-base
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model-index:
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- name: flan-t5-base-AR-LORA-V1
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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-base-AR-LORA-V1 |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7887 |
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- Exact Match: 28.3 |
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- Gen Len: 3.592 |
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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: 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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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Exact Match | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-----------:|:-------:| |
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| 1.1717 | 1.0 | 625 | 0.9465 | 18.9 | 3.82 | |
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| 0.8167 | 2.0 | 1250 | 0.8975 | 17.9 | 3.923 | |
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| 0.9046 | 3.0 | 1875 | 0.8691 | 25.4 | 3.338 | |
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| 0.9501 | 4.0 | 2500 | 0.8624 | 17.8 | 3.978 | |
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| 0.884 | 5.0 | 3125 | 0.8469 | 19.9 | 3.917 | |
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| 0.8418 | 6.0 | 3750 | 0.8356 | 24.8 | 3.596 | |
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| 0.877 | 7.0 | 4375 | 0.8261 | 19.0 | 3.926 | |
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| 0.804 | 8.0 | 5000 | 0.8147 | 23.0 | 3.732 | |
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| 0.8267 | 9.0 | 5625 | 0.8123 | 26.0 | 3.629 | |
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| 0.8979 | 10.0 | 6250 | 0.8132 | 24.5 | 3.685 | |
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| 0.8165 | 11.0 | 6875 | 0.8084 | 28.4 | 3.517 | |
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| 0.891 | 12.0 | 7500 | 0.8034 | 28.1 | 3.548 | |
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| 0.768 | 13.0 | 8125 | 0.8095 | 29.1 | 3.45 | |
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| 0.6895 | 14.0 | 8750 | 0.8018 | 27.7 | 3.553 | |
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| 0.7796 | 15.0 | 9375 | 0.7996 | 30.1 | 3.49 | |
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| 0.787 | 16.0 | 10000 | 0.8013 | 26.0 | 3.665 | |
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| 0.811 | 17.0 | 10625 | 0.7979 | 28.5 | 3.563 | |
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| 0.7858 | 18.0 | 11250 | 0.7991 | 26.4 | 3.64 | |
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| 0.8608 | 19.0 | 11875 | 0.7955 | 24.8 | 3.733 | |
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| 0.9044 | 20.0 | 12500 | 0.7913 | 25.9 | 3.662 | |
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| 0.9171 | 21.0 | 13125 | 0.7905 | 25.9 | 3.708 | |
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| 0.8093 | 22.0 | 13750 | 0.7918 | 28.1 | 3.596 | |
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| 0.7653 | 23.0 | 14375 | 0.7940 | 28.3 | 3.586 | |
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| 0.9361 | 24.0 | 15000 | 0.7887 | 28.3 | 3.592 | |
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| 0.6999 | 25.0 | 15625 | 0.7921 | 29.6 | 3.552 | |
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| 0.728 | 26.0 | 16250 | 0.7918 | 27.8 | 3.621 | |
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| 0.7169 | 27.0 | 16875 | 0.7908 | 27.2 | 3.628 | |
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| 0.6388 | 28.0 | 17500 | 0.7920 | 28.9 | 3.572 | |
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| 0.7302 | 29.0 | 18125 | 0.7920 | 28.8 | 3.573 | |
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| 0.7651 | 30.0 | 18750 | 0.7917 | 28.0 | 3.599 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.2 |
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- Pytorch 2.2.1 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
