qwen_jeopardy / README.md
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qwen-final-jeopardy
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metadata
base_model: Qwen/Qwen-14B
tags:
  - generated_from_trainer
datasets:
  - jeopardy
model-index:
  - name: final_jeopardy
    results: []

final_jeopardy

This model is a fine-tuned version of Qwen/Qwen-14B on the jeopardy dataset. It achieves the following results on the evaluation set:

  • Loss: 2.3619

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 0.01
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
3.0584 0.02 100 2.6536
2.6474 0.04 200 2.5669
2.5729 0.06 300 2.5225
2.5364 0.08 400 2.5054
2.4918 0.1 500 2.4876
2.502 0.12 600 2.4734
2.4993 0.14 700 2.4651
2.4982 0.16 800 2.4514
2.4676 0.18 900 2.4419
2.4414 0.2 1000 2.4396
2.4656 0.22 1100 2.4292
2.4795 0.24 1200 2.4250
2.4341 0.26 1300 2.4228
2.4276 0.28 1400 2.4157
2.4297 0.3 1500 2.4105
2.4617 0.32 1600 2.4084
2.4431 0.34 1700 2.4016
2.4037 0.36 1800 2.4002
2.4289 0.38 1900 2.3984
2.4351 0.4 2000 2.3922
2.3931 0.42 2100 2.3920
2.4253 0.44 2200 2.3892
2.4507 0.46 2300 2.3856
2.4063 0.48 2400 2.3846
2.4253 0.5 2500 2.3825
2.3948 0.52 2600 2.3778
2.3839 0.54 2700 2.3781
2.4304 0.56 2800 2.3799
2.4458 0.58 2900 2.3723
2.4051 0.6 3000 2.3733
2.3984 0.62 3100 2.3713
2.3886 0.64 3200 2.3702
2.3625 0.66 3300 2.3717
2.3745 0.68 3400 2.3676
2.4168 0.7 3500 2.3665
2.3761 0.72 3600 2.3669
2.379 0.74 3700 2.3662
2.3801 0.76 3800 2.3642
2.3817 0.78 3900 2.3640
2.4002 0.8 4000 2.3645
2.3989 0.82 4100 2.3635
2.3916 0.84 4200 2.3629
2.4045 0.86 4300 2.3624
2.3919 0.88 4400 2.3626
2.3943 0.9 4500 2.3626
2.3896 0.92 4600 2.3616
2.3518 0.94 4700 2.3621
2.41 0.96 4800 2.3616
2.3782 0.98 4900 2.3621
2.3589 1.0 5000 2.3619

Framework versions

  • Transformers 4.32.0
  • Pytorch 2.1.0
  • Datasets 2.14.7
  • Tokenizers 0.13.3