lmind_nq_train6000_eval6489_v1_recite_qa_v3__home_aiops_zhuty_lm_indexer_data_tyzhu_lmin
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4657
- Accuracy: 0.7995
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 20.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.4253 | 1.0 | 529 | 0.5042 | 0.7770 |
0.3444 | 2.0 | 1058 | 0.4371 | 0.7875 |
0.2679 | 3.0 | 1587 | 0.3925 | 0.7946 |
0.2195 | 4.0 | 2116 | 0.3709 | 0.7977 |
0.1889 | 5.0 | 2645 | 0.3616 | 0.7998 |
0.1724 | 6.0 | 3174 | 0.3608 | 0.8002 |
0.1573 | 7.0 | 3703 | 0.3646 | 0.8006 |
0.144 | 8.0 | 4232 | 0.3774 | 0.8000 |
0.1353 | 9.0 | 4761 | 0.3889 | 0.8000 |
0.1281 | 10.0 | 5290 | 0.3975 | 0.8000 |
0.124 | 11.0 | 5819 | 0.4108 | 0.7998 |
0.1169 | 12.0 | 6348 | 0.4183 | 0.8001 |
0.1128 | 13.0 | 6877 | 0.4249 | 0.7997 |
0.1108 | 14.0 | 7406 | 0.4259 | 0.8004 |
0.1078 | 15.0 | 7935 | 0.4435 | 0.7994 |
0.1065 | 16.0 | 8464 | 0.4421 | 0.7999 |
0.104 | 17.0 | 8993 | 0.4450 | 0.7998 |
0.103 | 18.0 | 9522 | 0.4554 | 0.7995 |
0.1033 | 19.0 | 10051 | 0.4556 | 0.7997 |
0.1041 | 20.0 | 10580 | 0.4657 | 0.7995 |
Framework versions
- PEFT 0.5.0
- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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