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sft

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

  • Loss: 0.4275

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: 1
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10.0

Training results

Training Loss Epoch Step Validation Loss
0.2064 4.4444 500 0.3316
0.0743 8.8889 1000 0.4199

Framework versions

  • PEFT 0.11.1
  • Transformers 4.43.2
  • Pytorch 2.3.1+rocm6.0
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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