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lmind_hotpot_train1000_eval500_v1_recite_qa_gpt2-xl

Text Generation
Transformers
PyTorch
gpt2
Generated from Trainer
Eval Results
text-generation-inference
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lmind_hotpot_train1000_eval500_v1_recite_qa_gpt2-xl / README.md
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metadata
license: mit
base_model: gpt2-xl
tags:
  - generated_from_trainer
datasets:
  - tyzhu/lmind_hotpot_train1000_eval500_v1_recite_qa
metrics:
  - accuracy
model-index:
  - name: lmind_hotpot_train1000_eval500_v1_recite_qa_gpt2-xl
    results:
      - task:
          name: Causal Language Modeling
          type: text-generation
        dataset:
          name: tyzhu/lmind_hotpot_train1000_eval500_v1_recite_qa
          type: tyzhu/lmind_hotpot_train1000_eval500_v1_recite_qa
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7496011644832605

lmind_hotpot_train1000_eval500_v1_recite_qa_gpt2-xl

This model is a fine-tuned version of gpt2-xl on the tyzhu/lmind_hotpot_train1000_eval500_v1_recite_qa dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4181
  • Accuracy: 0.7496

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: 3e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant
  • num_epochs: 20.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.9823 1.0 248 1.6149 0.6398
1.3868 2.0 496 1.1929 0.6700
0.9102 3.0 744 0.8513 0.6992
0.5869 4.0 992 0.6181 0.7218
0.364 5.0 1240 0.4963 0.7352
0.2706 6.0 1488 0.4413 0.7420
0.1906 7.0 1736 0.4085 0.7458
0.1474 8.0 1984 0.4010 0.7477
0.1264 9.0 2232 0.3979 0.7484
0.1091 10.0 2480 0.4060 0.7487
0.1072 11.0 2728 0.4050 0.7490
0.0969 12.0 2976 0.4081 0.7492
0.0935 13.0 3224 0.4145 0.7495
0.0932 14.0 3472 0.4078 0.7494
0.0929 15.0 3720 0.4140 0.7494
0.0951 16.0 3968 0.4145 0.7495
0.0926 17.0 4216 0.4134 0.7495
0.0946 18.0 4464 0.4257 0.7493
0.0897 19.0 4712 0.4164 0.7496
0.092 20.0 4960 0.4181 0.7496

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.5
  • Tokenizers 0.14.1