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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_doc_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_doc_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_doc_qa_v3 |
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type: tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.560974358974359 |
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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_doc_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_doc_qa_v3 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2417 |
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- Accuracy: 0.5610 |
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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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| 1.8583 | 1.0 | 529 | 1.6376 | 0.5726 | |
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| 1.6329 | 2.0 | 1058 | 1.6881 | 0.5713 | |
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| 1.3464 | 3.0 | 1587 | 1.8256 | 0.5663 | |
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| 1.1624 | 4.0 | 2116 | 1.9223 | 0.5652 | |
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| 0.964 | 5.0 | 2645 | 1.9720 | 0.5643 | |
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| 0.8117 | 6.0 | 3174 | 2.0016 | 0.5647 | |
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| 0.7242 | 7.0 | 3703 | 2.0785 | 0.5639 | |
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| 0.6381 | 8.0 | 4232 | 2.0954 | 0.5645 | |
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| 0.573 | 9.0 | 4761 | 2.1067 | 0.5623 | |
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| 0.5269 | 10.0 | 5290 | 2.1356 | 0.5646 | |
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| 0.5144 | 11.0 | 5819 | 2.1951 | 0.5616 | |
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| 0.4887 | 12.0 | 6348 | 2.1779 | 0.5631 | |
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| 0.4636 | 13.0 | 6877 | 2.1757 | 0.5611 | |
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| 0.467 | 14.0 | 7406 | 2.1781 | 0.5624 | |
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| 0.4613 | 15.0 | 7935 | 2.2312 | 0.5612 | |
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| 0.4405 | 16.0 | 8464 | 2.1800 | 0.5629 | |
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| 0.4308 | 17.0 | 8993 | 2.1960 | 0.5628 | |
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| 0.4401 | 18.0 | 9522 | 2.2355 | 0.5610 | |
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| 0.4334 | 19.0 | 10051 | 2.2380 | 0.5608 | |
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| 0.4218 | 20.0 | 10580 | 2.2417 | 0.5610 | |
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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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