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lmind_hotpot_train8000_eval7405_v1_recite_qa_gpt2-xl

Text Generation
Transformers
PyTorch
gpt2
Generated from Trainer
Eval Results
text-generation-inference
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lmind_hotpot_train8000_eval7405_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_train8000_eval7405_v1_recite_qa
metrics:
  - accuracy
model-index:
  - name: lmind_hotpot_train8000_eval7405_v1_recite_qa_gpt2-xl
    results:
      - task:
          name: Causal Language Modeling
          type: text-generation
        dataset:
          name: tyzhu/lmind_hotpot_train8000_eval7405_v1_recite_qa
          type: tyzhu/lmind_hotpot_train8000_eval7405_v1_recite_qa
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7664424114149346

lmind_hotpot_train8000_eval7405_v1_recite_qa_gpt2-xl

This model is a fine-tuned version of gpt2-xl on the tyzhu/lmind_hotpot_train8000_eval7405_v1_recite_qa dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4650
  • Accuracy: 0.7664

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
1.9537 1.0 2179 0.6693 1.5623
1.4734 2.0 4358 0.6924 1.2099
1.0665 3.0 6537 0.7147 0.9178
0.7684 4.0 8716 0.7331 0.6988
0.548 5.0 10895 0.7466 0.5567
0.4039 6.0 13074 0.7551 0.4728
0.3044 7.0 15253 0.7600 0.4376
0.2446 8.0 17432 0.7628 0.4220
0.2039 9.0 19611 0.7642 0.4190
0.1787 10.0 21790 0.7649 0.4250
0.1652 11.0 23969 0.7654 0.4295
0.154 12.0 26148 0.7655 0.4366
0.1441 13.0 28327 0.7657 0.4429
0.143 14.0 30506 0.7657 0.4418
0.1366 15.0 32685 0.7661 0.4469
0.1335 16.0 34864 0.7661 0.4517
0.1299 17.0 37043 0.7662 0.4534
0.1271 18.0 39222 0.7664 0.4579
0.1268 19.0 41401 0.7664 0.4556
0.1238 20.0 43580 0.4650 0.7664

Framework versions

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