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--- |
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language: |
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- zh |
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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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- nycu-112-2-deeplearning-hw2 |
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- generated_from_trainer |
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base_model: mistralai/Mistral-7B-Instruct-v0.2 |
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datasets: |
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- DandinPower/ZH-Reading-Comprehension-Mistral-Instruct |
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model-index: |
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- name: mistral_7b_lora_completion_only |
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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_7b_lora_completion_only |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the DandinPower/ZH-Reading-Comprehension-Mistral-Instruct dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1344 |
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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: 0.0001 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 2 |
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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: 700 |
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- num_epochs: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.1996 | 0.3690 | 250 | 0.1814 | |
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| 0.1856 | 0.7380 | 500 | 0.1344 | |
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| 0.1515 | 1.1070 | 750 | 0.1724 | |
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| 0.1547 | 1.4760 | 1000 | 0.1977 | |
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| 0.0953 | 1.8450 | 1250 | 0.1641 | |
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| 0.0788 | 2.2140 | 1500 | 0.1450 | |
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| 0.0715 | 2.5830 | 1750 | 0.1359 | |
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| 0.0646 | 2.9520 | 2000 | 0.1427 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.0 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
