README.md

metadata

base_model: meta-llama/Meta-Llama-3.1-8B
datasets:
  - wikitext
library_name: peft
license: llama3.1
metrics:
  - accuracy
tags:
  - generated_from_trainer
model-index:
  - name: wikitext_Meta-Llama-3.1-8B-BNB-NF4_LORA_ADAPTER_64rank
    results:
      - task:
          type: text-generation
          name: Causal Language Modeling
        dataset:
          name: wikitext wikitext-2-raw-v1
          type: wikitext
          args: wikitext-2-raw-v1
        metrics:
          - type: accuracy
            value: 0.5869990224828935
            name: Accuracy

wikitext_Meta-Llama-3.1-8B-BNB-NF4_LORA_ADAPTER_64rank

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the wikitext wikitext-2-raw-v1 dataset. It achieves the following results on the evaluation set:

• Loss: 2.3246
• Accuracy: 0.5870

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: 4
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• total_eval_batch_size: 8
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.03
• num_epochs: 3.0

Training results

Framework versions

• PEFT 0.13.2
• Transformers 4.46.3
• Pytorch 2.4.0+cu121
• Datasets 3.2.0
• Tokenizers 0.20.3