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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_docidx_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_hotpot_train8000_eval7405_v1_docidx_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: 1.0623
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- Accuracy: 0.7692
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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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| 1.6067 | 0.9997 | 839 | 1.8440 | 0.7197 |
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| 1.5433 | 1.9994 | 1678 | 1.7661 | 0.7247 |
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| 1.4167 | 2.9991 | 2517 | 1.6455 | 0.7310 |
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| 1.2948 | 4.0 | 3357 | 1.5394 | 0.7366 |
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| 1.1715 | 4.9997 | 4196 | 1.4463 | 0.7422 |
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| 1.0458 | 5.9994 | 5035 | 1.3537 | 0.7484 |
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| 0.9357 | 6.9991 | 5874 | 1.2456 | 0.7546 |
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| 0.8269 | 8.0 | 6714 | 1.1735 | 0.7598 |
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| 0.7262 | 8.9997 | 7553 | 1.0966 | 0.7649 |
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| 0.6381 | 9.9970 | 8390 | 1.0623 | 0.7692 |
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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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