Model save
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README.md
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---
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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_reciteonly_qa_v3_lora2
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results: []
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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_reciteonly_qa_v3_lora2
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This model was trained from scratch on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.3138
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- Accuracy: 0.6569
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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: 2
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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: 4
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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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| 1.0895 | 1.0 | 187 | 1.0317 | 0.6904 |
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| 0.9959 | 2.0 | 375 | 1.0319 | 0.6908 |
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| 0.9099 | 3.0 | 562 | 1.0512 | 0.6890 |
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| 0.7893 | 4.0 | 750 | 1.0986 | 0.6843 |
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| 0.674 | 5.0 | 937 | 1.1695 | 0.6794 |
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| 0.5518 | 6.0 | 1125 | 1.2677 | 0.6744 |
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| 0.4364 | 7.0 | 1312 | 1.3770 | 0.6708 |
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| 0.3384 | 8.0 | 1500 | 1.4781 | 0.6685 |
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| 0.2488 | 9.0 | 1687 | 1.6224 | 0.6652 |
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| 0.1889 | 10.0 | 1875 | 1.7546 | 0.6625 |
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| 0.1469 | 11.0 | 2062 | 1.8724 | 0.6613 |
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| 0.12 | 12.0 | 2250 | 1.9857 | 0.6595 |
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| 0.1016 | 13.0 | 2437 | 2.0585 | 0.6597 |
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| 0.0917 | 14.0 | 2625 | 2.1262 | 0.6584 |
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| 0.0867 | 15.0 | 2812 | 2.1983 | 0.6578 |
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| 0.0832 | 16.0 | 3000 | 2.2629 | 0.6573 |
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| 0.0765 | 17.0 | 3187 | 2.2393 | 0.6581 |
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| 0.0762 | 18.0 | 3375 | 2.2691 | 0.6576 |
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| 0.0761 | 19.0 | 3562 | 2.2851 | 0.6581 |
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| 0.0754 | 19.95 | 3740 | 2.3138 | 0.6569 |
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### Framework versions
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- Transformers 4.34.0
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- Pytorch 2.1.0+cu121
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- Datasets 2.18.0
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- Tokenizers 0.14.1
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