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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_doc_qa_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_hotpot_train8000_eval7405_v1_doc_qa_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: 3.1631 |
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- Accuracy: 0.5165 |
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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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| 1.7567 | 0.9998 | 1089 | 2.2626 | 0.5190 | |
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| 1.5617 | 1.9995 | 2178 | 2.2436 | 0.5246 | |
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| 1.343 | 2.9993 | 3267 | 2.3385 | 0.5237 | |
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| 1.1682 | 4.0 | 4357 | 2.4995 | 0.5215 | |
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| 1.0141 | 4.9998 | 5446 | 2.6397 | 0.5182 | |
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| 0.9023 | 5.9995 | 6535 | 2.7929 | 0.5170 | |
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| 0.8008 | 6.9993 | 7624 | 2.8233 | 0.5162 | |
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| 0.7377 | 8.0 | 8714 | 2.8833 | 0.5180 | |
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| 0.6732 | 8.9998 | 9803 | 2.9550 | 0.5165 | |
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| 0.6225 | 9.9995 | 10892 | 2.9767 | 0.5165 | |
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| 0.5858 | 10.9993 | 11981 | 3.0117 | 0.5165 | |
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| 0.5618 | 12.0 | 13071 | 3.0317 | 0.5170 | |
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| 0.5464 | 12.9998 | 14160 | 3.0686 | 0.5167 | |
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| 0.5243 | 13.9995 | 15249 | 3.0829 | 0.5149 | |
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| 0.5066 | 14.9993 | 16338 | 3.0958 | 0.5127 | |
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| 0.4947 | 16.0 | 17428 | 3.0921 | 0.5153 | |
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| 0.4841 | 16.9998 | 18517 | 3.1170 | 0.5162 | |
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| 0.4727 | 17.9995 | 19606 | 3.1375 | 0.5172 | |
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| 0.4634 | 18.9993 | 20695 | 3.1323 | 0.5150 | |
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| 0.4468 | 19.9954 | 21780 | 3.1631 | 0.5165 | |
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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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