Model save
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README.md
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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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metrics:
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- accuracy
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model-index:
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- name: lmind_nq_train6000_eval6489_v1_recite_qa_v3_Qwen_Qwen1.5-4B_5e-5_lora2
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results: []
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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_nq_train6000_eval6489_v1_recite_qa_v3_Qwen_Qwen1.5-4B_5e-5_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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5804
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- Accuracy: 0.7754
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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: 5e-05
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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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| 1.8478 | 1.0 | 529 | 1.6699 | 0.6080 |
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| 1.7862 | 2.0 | 1058 | 1.6003 | 0.6164 |
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| 1.6531 | 3.0 | 1587 | 1.5363 | 0.6251 |
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| 1.5515 | 4.0 | 2116 | 1.4608 | 0.6343 |
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| 1.4038 | 5.0 | 2645 | 1.3876 | 0.6456 |
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| 1.2751 | 6.0 | 3174 | 1.3186 | 0.6553 |
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| 1.1475 | 7.0 | 3703 | 1.2514 | 0.6637 |
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| 1.0282 | 8.0 | 4232 | 1.1740 | 0.676 |
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| 0.9067 | 9.0 | 4761 | 1.1004 | 0.6870 |
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| 0.8202 | 10.0 | 5290 | 1.0408 | 0.6964 |
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| 0.7007 | 11.0 | 5819 | 0.9592 | 0.7084 |
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| 0.6259 | 12.0 | 6348 | 0.8998 | 0.7191 |
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| 0.553 | 13.0 | 6877 | 0.8332 | 0.7295 |
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| 0.4948 | 14.0 | 7406 | 0.7799 | 0.7387 |
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| 0.4221 | 15.0 | 7935 | 0.7330 | 0.7466 |
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| 0.3911 | 16.0 | 8464 | 0.6805 | 0.7551 |
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| 0.3377 | 17.0 | 8993 | 0.6475 | 0.7620 |
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| 0.3179 | 18.0 | 9522 | 0.6195 | 0.7680 |
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| 0.288 | 19.0 | 10051 | 0.5962 | 0.7723 |
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| 0.2605 | 20.0 | 10580 | 0.5804 | 0.7754 |
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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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