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_qa_Qwen_Qwen1.5-4B_5e-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_nq_train6000_eval6489_v1_qa_Qwen_Qwen1.5-4B_5e-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: 2.5214
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- Accuracy: 0.5534
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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: 5e-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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| 1.8353 | 0.9973 | 187 | 1.6327 | 0.5719 |
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| 1.5773 | 2.0 | 375 | 1.6119 | 0.5743 |
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| 1.4151 | 2.9973 | 562 | 1.6409 | 0.5734 |
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| 1.226 | 4.0 | 750 | 1.7002 | 0.5688 |
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| 1.0718 | 4.9973 | 937 | 1.7919 | 0.5664 |
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| 0.9478 | 6.0 | 1125 | 1.8953 | 0.5631 |
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| 0.8356 | 6.9973 | 1312 | 1.9827 | 0.5607 |
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| 0.7482 | 8.0 | 1500 | 2.0659 | 0.5591 |
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| 0.6415 | 8.9973 | 1687 | 2.2042 | 0.5565 |
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| 0.6094 | 10.0 | 1875 | 2.2516 | 0.5552 |
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| 0.5807 | 10.9973 | 2062 | 2.2925 | 0.5554 |
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| 0.5647 | 12.0 | 2250 | 2.3210 | 0.5562 |
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| 0.5523 | 12.9973 | 2437 | 2.3624 | 0.556 |
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| 0.5417 | 14.0 | 2625 | 2.4357 | 0.5541 |
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| 0.5335 | 14.9973 | 2812 | 2.4554 | 0.5528 |
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| 0.5312 | 16.0 | 3000 | 2.4443 | 0.5553 |
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| 0.5001 | 16.9973 | 3187 | 2.4833 | 0.5533 |
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| 0.4992 | 18.0 | 3375 | 2.4588 | 0.5559 |
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| 0.5004 | 18.9973 | 3562 | 2.5082 | 0.5546 |
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| 0.4983 | 19.9467 | 3740 | 2.5214 | 0.5534 |
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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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