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Interview_L3_1000rate_1e5_SFT_SFT

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0253

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: 1e-05
  • train_batch_size: 2
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • training_steps: 1000

Training results

Training Loss Epoch Step Validation Loss
1.3904 0.0376 50 1.2452
1.1582 0.0752 100 0.9397
0.9079 0.1129 150 0.6367
0.3786 0.1505 200 0.4351
0.258 0.1881 250 0.3067
0.2163 0.2257 300 0.2114
0.1031 0.2634 350 0.1570
0.0911 0.3010 400 0.1205
0.0739 0.3386 450 0.0901
0.0503 0.3762 500 0.0713
0.0713 0.4138 550 0.0598
0.066 0.4515 600 0.0457
0.0181 0.4891 650 0.0403
0.015 0.5267 700 0.0358
0.0172 0.5643 750 0.0301
0.0314 0.6020 800 0.0267
0.0279 0.6396 850 0.0259
0.0133 0.6772 900 0.0254
0.0122 0.7148 950 0.0253
0.0126 0.7524 1000 0.0253

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.0.0+cu117
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Model size
8.03B params
Tensor type
FP16
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