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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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datasets: |
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- tyzhu/lmind_nq_train6000_eval6489_v1_recite_qa_v3 |
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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_recite_qa_v3_Qwen_Qwen1.5-4B_5e-4_lora2 |
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results: |
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- task: |
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name: Causal Language Modeling |
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type: text-generation |
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dataset: |
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name: tyzhu/lmind_nq_train6000_eval6489_v1_recite_qa_v3 |
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type: tyzhu/lmind_nq_train6000_eval6489_v1_recite_qa_v3 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7918744394618834 |
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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_recite_qa_v3_Qwen_Qwen1.5-4B_5e-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 the tyzhu/lmind_nq_train6000_eval6489_v1_recite_qa_v3 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4565 |
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- Accuracy: 0.7919 |
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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: 0.0005 |
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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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| 1.7331 | 1.0 | 529 | 1.4271 | 0.6365 | |
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| 1.3037 | 2.0 | 1058 | 1.0687 | 0.6846 | |
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| 0.8818 | 3.0 | 1587 | 0.8142 | 0.7216 | |
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| 0.6397 | 4.0 | 2116 | 0.6636 | 0.7470 | |
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| 0.4735 | 5.0 | 2645 | 0.5547 | 0.7667 | |
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| 0.3798 | 6.0 | 3174 | 0.5002 | 0.7764 | |
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| 0.3409 | 7.0 | 3703 | 0.4850 | 0.7801 | |
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| 0.3054 | 8.0 | 4232 | 0.4691 | 0.7835 | |
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| 0.2803 | 9.0 | 4761 | 0.4637 | 0.7859 | |
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| 0.2637 | 10.0 | 5290 | 0.4532 | 0.7877 | |
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| 0.2661 | 11.0 | 5819 | 0.4668 | 0.7879 | |
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| 0.2513 | 12.0 | 6348 | 0.4647 | 0.7893 | |
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| 0.2424 | 13.0 | 6877 | 0.4615 | 0.7897 | |
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| 0.2499 | 14.0 | 7406 | 0.4546 | 0.7894 | |
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| 0.235 | 15.0 | 7935 | 0.4668 | 0.7896 | |
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| 0.2317 | 16.0 | 8464 | 0.4510 | 0.7913 | |
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| 0.2225 | 17.0 | 8993 | 0.4497 | 0.7915 | |
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| 0.2358 | 18.0 | 9522 | 0.4475 | 0.7916 | |
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| 0.2253 | 19.0 | 10051 | 0.4529 | 0.7918 | |
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| 0.2172 | 20.0 | 10580 | 0.4565 | 0.7919 | |
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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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