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metadata
license: apache-2.0
library_name: peft
tags:
  - generated_from_trainer
base_model: TheBloke/Mistral-7B-Instruct-v0.1-GPTQ
model-index:
  - name: mistral-finetuned-samsum
    results: []

mistral-finetuned-samsum

This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.1-GPTQ on the None dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

The following bitsandbytes quantization config was used during training:

  • quant_method: gptq
  • bits: 4
  • tokenizer: None
  • dataset: None
  • group_size: 128
  • damp_percent: 0.1
  • desc_act: True
  • sym: True
  • true_sequential: True
  • use_cuda_fp16: False
  • model_seqlen: None
  • block_name_to_quantize: None
  • module_name_preceding_first_block: None
  • batch_size: 1
  • pad_token_id: None
  • use_exllama: False
  • max_input_length: None
  • exllama_config: {'version': <ExllamaVersion.ONE: 1>}
  • cache_block_outputs: True

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • training_steps: 50
  • mixed_precision_training: Native AMP

Training results

Framework versions

  • PEFT 0.7.0
  • Transformers 4.36.0.dev0
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0