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zephyr-chatbot

This model is a fine-tuned version of TheBloke/zephyr-7B-alpha-GPTQ on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8794

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: 4095
  • block_name_to_quantize: model.layers
  • module_name_preceding_first_block: ['model.embed_tokens']
  • 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: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.9364 1.0 121 0.9402
0.8289 2.0 242 0.8849
0.7249 3.0 363 0.8540
0.6322 4.0 484 0.8387
0.5337 5.0 605 0.8475
0.4523 6.0 726 0.8586
0.405 7.0 847 0.8698
0.3965 8.0 968 0.8794
0.3859 8.26 1000 0.8794

Framework versions

  • PEFT 0.7.0
  • Transformers 4.36.0.dev0
  • Pytorch 2.1.1+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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