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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/mistral-7b-instruct-v0.2-bnb-4bit |
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model-index: |
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- name: mistral-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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# mistral-QA-ViMMRC-Squad-v1.1 |
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This model is a fine-tuned version of [unsloth/mistral-7b-instruct-v0.2-bnb-4bit](https://huggingface.co/unsloth/mistral-7b-instruct-v0.2-bnb-4bit) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0484 |
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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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| 1.0039 | 0.2307 | 320 | 1.4915 | |
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| 0.8101 | 0.4614 | 640 | 1.5005 | |
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| 0.6909 | 0.6921 | 960 | 1.5480 | |
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| 0.5851 | 0.9229 | 1280 | 1.5734 | |
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| 0.4374 | 1.1536 | 1600 | 1.6432 | |
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| 0.3462 | 1.3843 | 1920 | 1.6886 | |
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| 0.2845 | 1.6150 | 2240 | 1.7347 | |
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| 0.2236 | 1.8457 | 2560 | 1.8193 | |
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| 0.158 | 2.0764 | 2880 | 1.9148 | |
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| 0.1124 | 2.3071 | 3200 | 1.9873 | |
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| 0.0981 | 2.5379 | 3520 | 2.0051 | |
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| 0.0892 | 2.7686 | 3840 | 2.0392 | |
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| 0.0856 | 2.9993 | 4160 | 2.0484 | |
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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 |
