End of training

README.md

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+---
+language:
+- zh
+license: other
+library_name: peft
+tags:
+- trl
+- sft
+- nycu-112-2-deeplearning-hw2
+- generated_from_trainer
+base_model: meta-llama/Meta-Llama-3-8B-Instruct
+datasets:
+- DandinPower/ZH-Reading-Comprehension-Llama-Instruct
+model-index:
+- name: llama_3_8b_lora_completion_only
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# llama_3_8b_lora_completion_only
+
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the DandinPower/ZH-Reading-Comprehension-Llama-Instruct dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0924
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 16
+- total_eval_batch_size: 2
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 700
+- num_epochs: 5.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.105         | 0.3690 | 250  | 0.0762          |
+| 0.0716        | 0.7380 | 500  | 0.0897          |
+| 0.0652        | 1.1070 | 750  | 0.0832          |
+| 0.061         | 1.4760 | 1000 | 0.0640          |
+| 0.0373        | 1.8450 | 1250 | 0.0813          |
+| 0.0344        | 2.2140 | 1500 | 0.0686          |
+| 0.0207        | 2.5830 | 1750 | 0.0662          |
+| 0.0351        | 2.9520 | 2000 | 0.0669          |
+| 0.0028        | 3.3210 | 2250 | 0.0996          |
+| 0.0101        | 3.6900 | 2500 | 0.0718          |
+| 0.0044        | 4.0590 | 2750 | 0.0825          |
+| 0.0123        | 4.4280 | 3000 | 0.0969          |
+| 0.0031        | 4.7970 | 3250 | 0.0924          |
+
+
+### Framework versions
+
+- PEFT 0.10.0
+- Transformers 4.40.0
+- Pytorch 2.2.2+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

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