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_reciteonly_qa_v3_Qwen_Qwen1.5-4B_3e-4_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_reciteonly_qa_v3_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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.0184
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- Accuracy: 0.5886
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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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| 1.7516 | 0.9973 | 187 | 1.6714 | 0.6086 |
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| 1.5219 | 2.0 | 375 | 1.6736 | 0.6104 |
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| 1.2037 | 2.9973 | 562 | 1.7561 | 0.6081 |
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| 0.8815 | 4.0 | 750 | 1.8875 | 0.6033 |
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| 0.6016 | 4.9973 | 937 | 2.0768 | 0.5980 |
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| 0.3979 | 6.0 | 1125 | 2.2606 | 0.5953 |
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| 0.2591 | 6.9973 | 1312 | 2.4670 | 0.5933 |
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| 0.1821 | 8.0 | 1500 | 2.6145 | 0.5922 |
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| 0.1338 | 8.9973 | 1687 | 2.7399 | 0.5911 |
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| 0.1172 | 10.0 | 1875 | 2.8330 | 0.5915 |
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| 0.1102 | 10.9973 | 2062 | 2.8674 | 0.5914 |
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| 0.1079 | 12.0 | 2250 | 2.8947 | 0.5903 |
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| 0.11 | 12.9973 | 2437 | 2.9230 | 0.5894 |
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| 0.1136 | 14.0 | 2625 | 2.9049 | 0.5888 |
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| 0.1173 | 14.9973 | 2812 | 2.8788 | 0.5883 |
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| 0.1163 | 16.0 | 3000 | 2.9582 | 0.5892 |
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| 0.1047 | 16.9973 | 3187 | 2.9485 | 0.5886 |
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| 0.1044 | 18.0 | 3375 | 2.9815 | 0.5894 |
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| 0.105 | 18.9973 | 3562 | 2.9880 | 0.5881 |
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| 0.1036 | 19.9467 | 3740 | 3.0184 | 0.5886 |
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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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