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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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- trl |
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- sft |
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- unsloth |
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- generated_from_trainer |
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base_model: unsloth/llama-3-8b-Instruct-bnb-4bit |
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model-index: |
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- name: llama3-QA-ViMMRC-Squad-v1.1 |
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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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# llama3-QA-ViMMRC-Squad-v1.1 |
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This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct-bnb-4bit](https://huggingface.co./unsloth/llama-3-8b-Instruct-bnb-4bit) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6506 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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- **Prompt 1**: Given the following reference, create a question and a corresponding answer to the question: + [context] |
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- **Prompt 2**: Given the following reference, create a multiple-choice question and its corresponding answer: + [context] |
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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: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 3407 |
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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: cosine |
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- lr_scheduler_warmup_steps: 5 |
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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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| 1.8259 | 0.2307 | 320 | 1.8769 | |
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| 1.611 | 0.4614 | 640 | 1.9125 | |
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| 1.4266 | 0.6921 | 960 | 1.9795 | |
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| 1.2355 | 0.9229 | 1280 | 2.0370 | |
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| 0.9715 | 1.1536 | 1600 | 2.1435 | |
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| 0.7983 | 1.3843 | 1920 | 2.2154 | |
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| 0.6768 | 1.6150 | 2240 | 2.3018 | |
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| 0.5643 | 1.8457 | 2560 | 2.3872 | |
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| 0.4374 | 2.0764 | 2880 | 2.5030 | |
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| 0.325 | 2.3071 | 3200 | 2.5655 | |
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| 0.2927 | 2.5379 | 3520 | 2.6038 | |
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| 0.2688 | 2.7686 | 3840 | 2.6470 | |
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| 0.2641 | 2.9993 | 4160 | 2.6506 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
