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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_docidx_v3_Qwen_Qwen1.5-4B_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_docidx_v3_Qwen_Qwen1.5-4B_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: 4.5794
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- Accuracy: 0.4488
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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: 0.0001
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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: 10.0
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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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| 1.9569 | 0.9985 | 341 | 3.0300 | 0.4736 |
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| 1.8799 | 2.0 | 683 | 3.0993 | 0.468 |
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| 1.7649 | 2.9985 | 1024 | 3.2750 | 0.4650 |
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| 1.6077 | 4.0 | 1366 | 3.4406 | 0.4625 |
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| 1.4321 | 4.9985 | 1707 | 3.6500 | 0.4586 |
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| 1.2382 | 6.0 | 2049 | 3.8598 | 0.4562 |
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| 1.0525 | 6.9985 | 2390 | 4.0638 | 0.4541 |
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| 0.8607 | 8.0 | 2732 | 4.2389 | 0.4515 |
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| 0.7099 | 8.9985 | 3073 | 4.3484 | 0.4516 |
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| 0.5823 | 9.9854 | 3410 | 4.5794 | 0.4488 |
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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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