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--- |
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license: other |
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base_model: Qwen/Qwen1.5-4B |
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tags: |
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- generated_from_trainer |
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datasets: |
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- tyzhu/lmind_hotpot_train8000_eval7405_v1_qa |
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metrics: |
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- accuracy |
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model-index: |
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- name: lmind_hotpot_train8000_eval7405_v1_qa_Qwen_Qwen1.5-4B_5e-4_lora2 |
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results: |
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- task: |
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name: Causal Language Modeling |
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type: text-generation |
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dataset: |
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name: tyzhu/lmind_hotpot_train8000_eval7405_v1_qa |
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type: tyzhu/lmind_hotpot_train8000_eval7405_v1_qa |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.48644444444444446 |
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library_name: peft |
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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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# lmind_hotpot_train8000_eval7405_v1_qa_Qwen_Qwen1.5-4B_5e-4_lora2 |
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This model is a fine-tuned version of [Qwen/Qwen1.5-4B](https://huggingface.co/Qwen/Qwen1.5-4B) on the tyzhu/lmind_hotpot_train8000_eval7405_v1_qa dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.7344 |
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- Accuracy: 0.4864 |
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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: 0.0005 |
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- train_batch_size: 1 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 20.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 2.252 | 1.0 | 250 | 2.3165 | 0.5171 | |
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| 1.8363 | 2.0 | 500 | 2.4264 | 0.5127 | |
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| 1.3801 | 3.0 | 750 | 2.6120 | 0.5059 | |
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| 1.0246 | 4.0 | 1000 | 2.8617 | 0.5008 | |
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| 0.7286 | 5.0 | 1250 | 3.0953 | 0.4959 | |
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| 0.601 | 6.0 | 1500 | 3.2139 | 0.4950 | |
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| 0.5138 | 7.0 | 1750 | 3.2912 | 0.4933 | |
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| 0.4837 | 8.0 | 2000 | 3.4517 | 0.49 | |
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| 0.4506 | 9.0 | 2250 | 3.4107 | 0.4911 | |
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| 0.4578 | 10.0 | 2500 | 3.4786 | 0.4905 | |
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| 0.4362 | 11.0 | 2750 | 3.5410 | 0.4899 | |
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| 0.4429 | 12.0 | 3000 | 3.5656 | 0.4909 | |
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| 0.4366 | 13.0 | 3250 | 3.5425 | 0.4890 | |
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| 0.4474 | 14.0 | 3500 | 3.5998 | 0.4900 | |
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| 0.4283 | 15.0 | 3750 | 3.6044 | 0.4870 | |
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| 0.4299 | 16.0 | 4000 | 3.6720 | 0.4882 | |
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| 0.4202 | 17.0 | 4250 | 3.6220 | 0.4860 | |
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| 0.4318 | 18.0 | 4500 | 3.6682 | 0.4875 | |
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| 0.4151 | 19.0 | 4750 | 3.7105 | 0.4857 | |
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| 0.4227 | 20.0 | 5000 | 3.7344 | 0.4864 | |
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### Framework versions |
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- PEFT 0.5.0 |
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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 |
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