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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_reciteonly_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_reciteonly_qa_Qwen_Qwen1.5-4B_3e-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_reciteonly_qa |
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type: tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.6608966521106259 |
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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_reciteonly_qa_Qwen_Qwen1.5-4B_3e-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_reciteonly_qa dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7813 |
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- Accuracy: 0.6609 |
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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: 0.0003 |
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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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| 1.4488 | 1.0 | 250 | 1.4958 | 0.6770 | |
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| 1.3142 | 2.0 | 500 | 1.5007 | 0.6772 | |
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| 1.1176 | 3.0 | 750 | 1.5507 | 0.6756 | |
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| 0.9253 | 4.0 | 1000 | 1.6442 | 0.6728 | |
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| 0.7213 | 5.0 | 1250 | 1.7736 | 0.6701 | |
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| 0.5718 | 6.0 | 1500 | 1.8863 | 0.6682 | |
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| 0.4232 | 7.0 | 1750 | 2.0245 | 0.6660 | |
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| 0.3334 | 8.0 | 2000 | 2.1773 | 0.6642 | |
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| 0.2433 | 9.0 | 2250 | 2.2681 | 0.6632 | |
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| 0.2076 | 10.0 | 2500 | 2.3732 | 0.6629 | |
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| 0.1632 | 11.0 | 2750 | 2.4368 | 0.6623 | |
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| 0.1491 | 12.0 | 3000 | 2.5182 | 0.6617 | |
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| 0.1275 | 13.0 | 3250 | 2.5680 | 0.6619 | |
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| 0.1273 | 14.0 | 3500 | 2.6412 | 0.6613 | |
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| 0.1129 | 15.0 | 3750 | 2.6497 | 0.6617 | |
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| 0.1129 | 16.0 | 4000 | 2.6932 | 0.6614 | |
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| 0.102 | 17.0 | 4250 | 2.7003 | 0.6612 | |
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| 0.1109 | 18.0 | 4500 | 2.7033 | 0.6614 | |
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| 0.0997 | 19.0 | 4750 | 2.7139 | 0.6613 | |
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| 0.1012 | 20.0 | 5000 | 2.7813 | 0.6609 | |
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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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