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lmind_hotpot_train5000_eval5000_v1_recite_qa_gpt2-xl

Text Generation
Transformers
PyTorch
gpt2
Generated from Trainer
Eval Results
text-generation-inference
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lmind_hotpot_train5000_eval5000_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_train5000_eval5000_v1_recite_qa
metrics:
  - accuracy
model-index:
  - name: lmind_hotpot_train5000_eval5000_v1_recite_qa_gpt2-xl
    results:
      - task:
          name: Causal Language Modeling
          type: text-generation
        dataset:
          name: tyzhu/lmind_hotpot_train5000_eval5000_v1_recite_qa
          type: tyzhu/lmind_hotpot_train5000_eval5000_v1_recite_qa
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7660672947510094

lmind_hotpot_train5000_eval5000_v1_recite_qa_gpt2-xl

This model is a fine-tuned version of gpt2-xl on the tyzhu/lmind_hotpot_train5000_eval5000_v1_recite_qa dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4522
  • Accuracy: 0.7661

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 Accuracy Validation Loss
1.9686 1.0 1452 0.6681 1.5662
1.4604 2.0 2904 0.6915 1.2069
1.0522 3.0 4356 0.7149 0.9046
0.7455 4.0 5808 0.7341 0.6844
0.5307 5.0 7260 0.7475 0.5420
0.3796 6.0 8712 0.7560 0.4609
0.2912 7.0 10164 0.7604 0.4311
0.2282 8.0 11616 0.7627 0.4184
0.1905 9.0 13068 0.7640 0.4136
0.1687 10.0 14520 0.7648 0.4175
0.1553 11.0 15972 0.7651 0.4212
0.1447 12.0 17424 0.7653 0.4283
0.1388 13.0 18876 0.7656 0.4287
0.1329 14.0 20328 0.7657 0.4349
0.1292 15.0 21780 0.7657 0.4353
0.1267 16.0 23232 0.7659 0.4383
0.1251 17.0 24684 0.4416 0.7661
0.1201 18.0 26136 0.4467 0.7659
0.1186 19.0 27588 0.4508 0.7660
0.1176 20.0 29040 0.4522 0.7661

Framework versions

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