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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: flan-t5-base_Adapters |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/dhanishetty-personaluse/huggingface/runs/1ojupjbx) |
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# flan-t5-base_Adapters |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0702 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: inverse_sqrt |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.6034 | 0.1688 | 50 | 1.3534 | |
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| 1.44 | 0.3376 | 100 | 1.2534 | |
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| 1.39 | 0.5063 | 150 | 1.2045 | |
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| 1.3075 | 0.6751 | 200 | 1.1710 | |
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| 1.2984 | 0.8439 | 250 | 1.1482 | |
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| 1.2933 | 1.0127 | 300 | 1.1500 | |
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| 1.2286 | 1.1814 | 350 | 1.1385 | |
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| 1.206 | 1.3502 | 400 | 1.1237 | |
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| 1.2097 | 1.5190 | 450 | 1.1112 | |
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| 1.1982 | 1.6878 | 500 | 1.1074 | |
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| 1.2451 | 1.8565 | 550 | 1.0894 | |
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| 1.1447 | 2.0253 | 600 | 1.1006 | |
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| 1.1324 | 2.1941 | 650 | 1.0787 | |
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| 1.137 | 2.3629 | 700 | 1.0798 | |
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| 1.14 | 2.5316 | 750 | 1.0739 | |
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| 1.1112 | 2.7004 | 800 | 1.0694 | |
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| 1.1436 | 2.8692 | 850 | 1.0702 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.43.2 |
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- Pytorch 2.1.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
