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--- |
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base_model: google/flan-t5-base |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: results |
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results: [] |
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pipeline_tag: text-generation |
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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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# results |
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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: 1.9615 |
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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: 0.001 |
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- train_batch_size: 6 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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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- lr_scheduler_warmup_steps: 23 |
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- training_steps: 2373 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 3.0035 | 0.42 | 50 | 2.5115 | |
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| 2.7023 | 0.84 | 100 | 2.3978 | |
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| 2.6198 | 1.26 | 150 | 2.3258 | |
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| 2.5523 | 1.68 | 200 | 2.2768 | |
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| 2.4817 | 2.1 | 250 | 2.2360 | |
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| 2.4591 | 2.52 | 300 | 2.2041 | |
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| 2.4 | 2.94 | 350 | 2.1844 | |
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| 2.3709 | 3.36 | 400 | 2.1547 | |
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| 2.3591 | 3.78 | 450 | 2.1366 | |
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| 2.3232 | 4.2 | 500 | 2.1210 | |
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| 2.3016 | 4.62 | 550 | 2.1119 | |
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| 2.3041 | 5.04 | 600 | 2.0993 | |
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| 2.2646 | 5.46 | 650 | 2.0908 | |
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| 2.247 | 5.88 | 700 | 2.0794 | |
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| 2.1935 | 6.3 | 750 | 2.0612 | |
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| 2.2334 | 6.72 | 800 | 2.0573 | |
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| 2.2054 | 7.14 | 850 | 2.0498 | |
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| 2.212 | 7.56 | 900 | 2.0460 | |
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| 2.1687 | 7.98 | 950 | 2.0388 | |
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| 2.1454 | 8.4 | 1000 | 2.0347 | |
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| 2.1344 | 8.82 | 1050 | 2.0243 | |
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| 2.1522 | 9.24 | 1100 | 2.0155 | |
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| 2.1051 | 9.66 | 1150 | 2.0144 | |
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| 2.1435 | 10.08 | 1200 | 2.0152 | |
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| 2.1251 | 10.5 | 1250 | 2.0133 | |
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| 2.0664 | 10.92 | 1300 | 2.0000 | |
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| 2.0656 | 11.34 | 1350 | 2.0002 | |
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| 2.1186 | 11.76 | 1400 | 1.9933 | |
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| 2.0719 | 12.18 | 1450 | 1.9906 | |
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| 2.0389 | 12.61 | 1500 | 1.9913 | |
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| 2.0655 | 13.03 | 1550 | 1.9874 | |
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| 2.0371 | 13.45 | 1600 | 1.9824 | |
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| 2.0581 | 13.87 | 1650 | 1.9789 | |
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| 2.0068 | 14.29 | 1700 | 1.9801 | |
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| 2.0536 | 14.71 | 1750 | 1.9750 | |
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| 2.0311 | 15.13 | 1800 | 1.9729 | |
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| 2.0292 | 15.55 | 1850 | 1.9716 | |
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| 1.9955 | 15.97 | 1900 | 1.9714 | |
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| 2.0056 | 16.39 | 1950 | 1.9671 | |
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| 2.0391 | 16.81 | 2000 | 1.9642 | |
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| 2.0059 | 17.23 | 2050 | 1.9687 | |
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| 2.0155 | 17.65 | 2100 | 1.9644 | |
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| 1.9745 | 18.07 | 2150 | 1.9617 | |
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| 1.9929 | 18.49 | 2200 | 1.9621 | |
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| 1.9978 | 18.91 | 2250 | 1.9639 | |
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| 2.023 | 19.33 | 2300 | 1.9617 | |
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| 1.992 | 19.75 | 2350 | 1.9615 | |
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### Framework versions |
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- PEFT 0.8.2 |
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- Transformers 4.38.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
