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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_hotpot_train8000_eval7405_v1_recite_qa_Qwen_Qwen1.5-4B_3e-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_hotpot_train8000_eval7405_v1_recite_qa_Qwen_Qwen1.5-4B_3e-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: 0.9440
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- Accuracy: 0.7263
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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: 3e-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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| 1.584 | 0.9998 | 1089 | 1.5103 | 0.6762 |
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| 1.5504 | 1.9995 | 2178 | 1.4772 | 0.6791 |
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| 1.4842 | 2.9993 | 3267 | 1.4502 | 0.6812 |
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| 1.427 | 4.0 | 4357 | 1.4200 | 0.6837 |
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| 1.3827 | 4.9998 | 5446 | 1.3911 | 0.6860 |
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| 1.3425 | 5.9995 | 6535 | 1.3615 | 0.6887 |
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| 1.2738 | 6.9993 | 7624 | 1.3300 | 0.6910 |
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| 1.2283 | 8.0 | 8714 | 1.3020 | 0.6935 |
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| 1.1788 | 8.9998 | 9803 | 1.2722 | 0.6963 |
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| 1.1156 | 9.9995 | 10892 | 1.2415 | 0.6990 |
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| 1.0526 | 10.9993 | 11981 | 1.2131 | 0.7015 |
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| 1.0146 | 12.0 | 13071 | 1.1804 | 0.7045 |
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| 0.9613 | 12.9998 | 14160 | 1.1508 | 0.7071 |
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| 0.9109 | 13.9995 | 15249 | 1.1214 | 0.7097 |
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| 0.8566 | 14.9993 | 16338 | 1.0913 | 0.7128 |
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| 0.8307 | 16.0 | 17428 | 1.0599 | 0.7156 |
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| 0.7803 | 16.9998 | 18517 | 1.0283 | 0.7184 |
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| 0.7486 | 17.9995 | 19606 | 0.9997 | 0.7215 |
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| 0.6992 | 18.9993 | 20695 | 0.9719 | 0.7238 |
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| 0.6632 | 19.9954 | 21780 | 0.9440 | 0.7263 |
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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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