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lmind_nq_train6000_eval6489_v1_reciteonly_qa_v3__home_aiops_zhuty_lm_indexer_data_tyzhu_

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@@ -6,6 +6,7 @@ metrics:
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  model-index:
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  - name: lmind_nq_train6000_eval6489_v1_reciteonly_qa_v3__home_aiops_zhuty_lm_indexer_data_tyzhu_
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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
@@ -15,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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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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- - Accuracy: 0.7597
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- - Loss: 0.8055
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  ## Model description
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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
@@ -51,33 +52,34 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Accuracy | Validation Loss |
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- |:-------------:|:-----:|:----:|:--------:|:---------------:|
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- | 0.5411 | 1.0 | 187 | 0.7904 | 0.3938 |
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- | 0.362 | 2.0 | 375 | 0.7918 | 0.3804 |
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- | 0.3047 | 3.0 | 562 | 0.7891 | 0.3934 |
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- | 0.2469 | 4.0 | 750 | 0.7846 | 0.4226 |
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- | 0.2022 | 5.0 | 937 | 0.7803 | 0.4661 |
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- | 0.1681 | 6.0 | 1125 | 0.7761 | 0.5123 |
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- | 0.1404 | 7.0 | 1312 | 0.7721 | 0.5731 |
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- | 0.1197 | 8.0 | 1500 | 0.7701 | 0.6075 |
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- | 0.1 | 9.0 | 1687 | 0.7688 | 0.6317 |
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- | 0.089 | 10.0 | 1875 | 0.7664 | 0.6718 |
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- | 0.0837 | 11.0 | 2062 | 0.7653 | 0.6922 |
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- | 0.0788 | 12.0 | 2250 | 0.7632 | 0.7254 |
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- | 0.0761 | 13.0 | 2437 | 0.7629 | 0.7256 |
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- | 0.0749 | 14.0 | 2625 | 0.7621 | 0.7534 |
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- | 0.0741 | 15.0 | 2812 | 0.7620 | 0.7529 |
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- | 0.0726 | 16.0 | 3000 | 0.7611 | 0.7678 |
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- | 0.0687 | 17.0 | 3187 | 0.7610 | 0.7728 |
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- | 0.0682 | 18.0 | 3375 | 0.7603 | 0.7807 |
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- | 0.0682 | 19.0 | 3562 | 0.7610 | 0.7872 |
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- | 0.0682 | 19.95 | 3740 | 0.7597 | 0.8055 |
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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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  model-index:
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  - name: lmind_nq_train6000_eval6489_v1_reciteonly_qa_v3__home_aiops_zhuty_lm_indexer_data_tyzhu_
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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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  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: 1.0955
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+ - Accuracy: 0.7196
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  ## Model description
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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: 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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | 0.7054 | 0.9973 | 187 | 0.5535 | 0.7686 |
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+ | 0.4975 | 2.0 | 375 | 0.5416 | 0.7693 |
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+ | 0.422 | 2.9973 | 562 | 0.5611 | 0.7645 |
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+ | 0.3527 | 4.0 | 750 | 0.6100 | 0.7573 |
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+ | 0.2941 | 4.9973 | 937 | 0.6599 | 0.7522 |
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+ | 0.2518 | 6.0 | 1125 | 0.7200 | 0.7458 |
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+ | 0.2138 | 6.9973 | 1312 | 0.7651 | 0.7421 |
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+ | 0.1824 | 8.0 | 1500 | 0.8280 | 0.7379 |
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+ | 0.1481 | 8.9973 | 1687 | 0.8700 | 0.7355 |
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+ | 0.1298 | 10.0 | 1875 | 0.9146 | 0.7329 |
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+ | 0.1167 | 10.9973 | 2062 | 0.9337 | 0.7309 |
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+ | 0.1094 | 12.0 | 2250 | 0.9733 | 0.7281 |
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+ | 0.1052 | 12.9973 | 2437 | 0.9980 | 0.7266 |
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+ | 0.1007 | 14.0 | 2625 | 1.0022 | 0.7256 |
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+ | 0.0971 | 14.9973 | 2812 | 1.0422 | 0.7234 |
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+ | 0.0954 | 16.0 | 3000 | 1.0441 | 0.7236 |
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+ | 0.0888 | 16.9973 | 3187 | 1.0574 | 0.7223 |
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+ | 0.0879 | 18.0 | 3375 | 1.0728 | 0.7216 |
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+ | 0.0879 | 18.9973 | 3562 | 1.0768 | 0.7200 |
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+ | 0.0883 | 19.9467 | 3740 | 1.0955 | 0.7196 |
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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