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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: MediaTek-Research/Breeze-7B-Instruct-v1_0 |
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datasets: |
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- DandinPower/ZH-Reading-Comprehension-Breeze-Instruct |
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model-index: |
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- name: breeze_7b_lora |
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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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# breeze_7b_lora |
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This model is a fine-tuned version of [MediaTek-Research/Breeze-7B-Instruct-v1_0](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-v1_0) on the DandinPower/ZH-Reading-Comprehension-Breeze-Instruct dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9671 |
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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: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.2919 | 0.3690 | 250 | 2.2932 | |
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| 2.2105 | 0.7380 | 500 | 2.1866 | |
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| 1.9287 | 1.1070 | 750 | 1.9796 | |
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| 1.8181 | 1.4760 | 1000 | 1.8416 | |
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| 1.6765 | 1.8450 | 1250 | 1.7156 | |
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| 1.4271 | 2.2140 | 1500 | 1.6054 | |
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| 1.3595 | 2.5830 | 1750 | 1.5071 | |
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| 1.2794 | 2.9520 | 2000 | 1.4263 | |
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| 1.0636 | 3.3210 | 2250 | 1.3707 | |
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| 1.0272 | 3.6900 | 2500 | 1.3044 | |
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| 0.8977 | 4.0590 | 2750 | 1.2597 | |
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| 0.8923 | 4.4280 | 3000 | 1.2184 | |
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| 0.8628 | 4.7970 | 3250 | 1.1737 | |
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| 0.6994 | 5.1661 | 3500 | 1.1514 | |
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| 0.7201 | 5.5351 | 3750 | 1.1209 | |
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| 0.7237 | 5.9041 | 4000 | 1.0931 | |
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| 0.6468 | 6.2731 | 4250 | 1.0740 | |
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| 0.6052 | 6.6421 | 4500 | 1.0472 | |
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| 0.5737 | 7.0111 | 4750 | 1.0360 | |
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| 0.5419 | 7.3801 | 5000 | 1.0246 | |
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| 0.5539 | 7.7491 | 5250 | 1.0027 | |
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| 0.4615 | 8.1181 | 5500 | 0.9947 | |
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| 0.4782 | 8.4871 | 5750 | 0.9851 | |
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| 0.4809 | 8.8561 | 6000 | 0.9699 | |
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| 0.4284 | 9.2251 | 6250 | 0.9738 | |
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| 0.4332 | 9.5941 | 6500 | 0.9696 | |
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| 0.4341 | 9.9631 | 6750 | 0.9671 | |
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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 |
