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lmind_nq_train6000_eval6489_v1_recite_qa_v3__home_aiops_zhuty_lm_indexer_data_tyzhu_lmin

PEFT
Safetensors
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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_recite_qa_v3__home_aiops_zhuty_lm_indexer_data_tyzhu_lmin
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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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- - Loss: 0.3984
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- - Accuracy: 0.8068
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  ## Model description
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@@ -36,12 +37,12 @@ More information needed
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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
@@ -53,31 +54,32 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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- | 0.2952 | 1.0 | 529 | 0.3721 | 0.7925 |
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- | 0.2481 | 2.0 | 1058 | 0.3231 | 0.8003 |
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- | 0.1935 | 3.0 | 1587 | 0.2963 | 0.8044 |
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- | 0.1593 | 4.0 | 2116 | 0.2872 | 0.8062 |
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- | 0.1405 | 5.0 | 2645 | 0.2908 | 0.8067 |
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- | 0.1235 | 6.0 | 3174 | 0.2929 | 0.8072 |
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- | 0.1154 | 7.0 | 3703 | 0.3109 | 0.8071 |
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- | 0.106 | 8.0 | 4232 | 0.3179 | 0.8069 |
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- | 0.0997 | 9.0 | 4761 | 0.3339 | 0.8071 |
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- | 0.095 | 10.0 | 5290 | 0.3424 | 0.8067 |
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- | 0.0922 | 11.0 | 5819 | 0.3516 | 0.8066 |
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- | 0.089 | 12.0 | 6348 | 0.3720 | 0.8063 |
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- | 0.0862 | 13.0 | 6877 | 0.3740 | 0.8065 |
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- | 0.0862 | 14.0 | 7406 | 0.3681 | 0.8070 |
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- | 0.0852 | 15.0 | 7935 | 0.3771 | 0.8067 |
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- | 0.0849 | 16.0 | 8464 | 0.3814 | 0.8066 |
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- | 0.083 | 17.0 | 8993 | 0.3799 | 0.8065 |
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- | 0.0838 | 18.0 | 9522 | 0.3887 | 0.8068 |
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- | 0.0834 | 19.0 | 10051 | 0.3909 | 0.8067 |
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- | 0.0818 | 20.0 | 10580 | 0.3984 | 0.8068 |
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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_recite_qa_v3__home_aiops_zhuty_lm_indexer_data_tyzhu_lmin
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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: 0.4657
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+ - Accuracy: 0.7995
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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 Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.4253 | 1.0 | 529 | 0.5042 | 0.7770 |
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+ | 0.3444 | 2.0 | 1058 | 0.4371 | 0.7875 |
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+ | 0.2679 | 3.0 | 1587 | 0.3925 | 0.7946 |
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+ | 0.2195 | 4.0 | 2116 | 0.3709 | 0.7977 |
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+ | 0.1889 | 5.0 | 2645 | 0.3616 | 0.7998 |
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+ | 0.1724 | 6.0 | 3174 | 0.3608 | 0.8002 |
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+ | 0.1573 | 7.0 | 3703 | 0.3646 | 0.8006 |
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+ | 0.144 | 8.0 | 4232 | 0.3774 | 0.8000 |
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+ | 0.1353 | 9.0 | 4761 | 0.3889 | 0.8000 |
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+ | 0.1281 | 10.0 | 5290 | 0.3975 | 0.8000 |
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+ | 0.124 | 11.0 | 5819 | 0.4108 | 0.7998 |
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+ | 0.1169 | 12.0 | 6348 | 0.4183 | 0.8001 |
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+ | 0.1128 | 13.0 | 6877 | 0.4249 | 0.7997 |
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+ | 0.1108 | 14.0 | 7406 | 0.4259 | 0.8004 |
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+ | 0.1078 | 15.0 | 7935 | 0.4435 | 0.7994 |
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+ | 0.1065 | 16.0 | 8464 | 0.4421 | 0.7999 |
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+ | 0.104 | 17.0 | 8993 | 0.4450 | 0.7998 |
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+ | 0.103 | 18.0 | 9522 | 0.4554 | 0.7995 |
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+ | 0.1033 | 19.0 | 10051 | 0.4556 | 0.7997 |
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+ | 0.1041 | 20.0 | 10580 | 0.4657 | 0.7995 |
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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