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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_qa_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_qa_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: 2.2527
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- Accuracy: 0.5594
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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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| 1.7657 | 0.9973 | 187 | 1.6215 | 0.5738 |
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| 1.497 | 2.0 | 375 | 1.6180 | 0.5742 |
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| 1.2345 | 2.9973 | 562 | 1.6951 | 0.5713 |
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| 1.0084 | 4.0 | 750 | 1.8059 | 0.5659 |
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| 0.8397 | 4.9973 | 937 | 1.9245 | 0.5647 |
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| 0.7186 | 6.0 | 1125 | 2.0345 | 0.5614 |
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| 0.6421 | 6.9973 | 1312 | 2.1148 | 0.5608 |
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| 0.5968 | 8.0 | 1500 | 2.1779 | 0.5585 |
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| 0.5417 | 8.9973 | 1687 | 2.2654 | 0.5568 |
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| 0.5356 | 9.9733 | 1870 | 2.2527 | 0.5594 |
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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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