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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: yentinglin/Taiwan-LLM-7B-v2.1-chat
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+ datasets:
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+ - DandinPower/ZH-Reading-Comprehension-TaiwanLlama-chat
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+ model-index:
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+ - name: taiwanllm_7b_lora_completion_only
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+ results: []
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+ ---
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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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+
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+ # taiwanllm_7b_lora_completion_only
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+
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+ This model is a fine-tuned version of [yentinglin/Taiwan-LLM-7B-v2.1-chat](https://huggingface.co/yentinglin/Taiwan-LLM-7B-v2.1-chat) on the DandinPower/ZH-Reading-Comprehension-TaiwanLlama-chat dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0867
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 0.1316 | 0.3690 | 250 | 0.1124 |
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+ | 0.0988 | 0.7380 | 500 | 0.1145 |
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+ | 0.0827 | 1.1070 | 750 | 0.0971 |
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+ | 0.0744 | 1.4760 | 1000 | 0.0897 |
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+ | 0.0482 | 1.8450 | 1250 | 0.0893 |
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+ | 0.0337 | 2.2140 | 1500 | 0.0924 |
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+ | 0.0229 | 2.5830 | 1750 | 0.0911 |
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+ | 0.0385 | 2.9520 | 2000 | 0.0867 |
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+
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+
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+ ### Framework versions
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+
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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