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: 250
• 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