ft-raft-hotpot / README.md
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finetuned-raft-hotpot-adapters
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metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
  - generator
library_name: peft
license: llama3.1
tags:
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: ft-raft-hotpot
    results: []

ft-raft-hotpot

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the generator dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8450

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: 0.0003
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 1399
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss
1.61 0.0148 20 1.3531
1.1917 0.0295 40 1.0786
1.0438 0.0443 60 1.0227
1.0087 0.0590 80 0.9971
0.9835 0.0738 100 0.9795
0.9753 0.0885 120 0.9651
0.9586 0.1033 140 0.9521
0.9504 0.1180 160 0.9419
0.937 0.1328 180 0.9312
0.9242 0.1475 200 0.9203
0.9073 0.1623 220 0.9111
0.9017 0.1771 240 0.9023
0.8956 0.1918 260 0.8939
0.8824 0.2066 280 0.8856
0.8776 0.2213 300 0.8784
0.8755 0.2361 320 0.8710
0.8746 0.2508 340 0.8646
0.8569 0.2656 360 0.8592
0.8499 0.2803 380 0.8547
0.8514 0.2951 400 0.8509
0.8541 0.3098 420 0.8484
0.856 0.3246 440 0.8465
0.8397 0.3394 460 0.8455
0.8402 0.3541 480 0.8451
0.8497 0.3689 500 0.8450

Framework versions

  • PEFT 0.12.0
  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1