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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_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_hotpot_train8000_eval7405_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: 3.4933
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- Accuracy: 0.4926
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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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| 2.2624 | 1.0 | 250 | 2.3220 | 0.5159 |
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| 2.0942 | 2.0 | 500 | 2.3289 | 0.5176 |
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| 1.8479 | 3.0 | 750 | 2.3997 | 0.5148 |
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| 1.6153 | 4.0 | 1000 | 2.5067 | 0.5107 |
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| 1.3618 | 5.0 | 1250 | 2.6641 | 0.5052 |
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| 1.1477 | 6.0 | 1500 | 2.8411 | 0.5016 |
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| 0.9248 | 7.0 | 1750 | 3.0246 | 0.4978 |
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| 0.7705 | 8.0 | 2000 | 3.2090 | 0.4954 |
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| 0.6344 | 9.0 | 2250 | 3.3400 | 0.4935 |
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| 0.5612 | 10.0 | 2500 | 3.4933 | 0.4926 |
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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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