healphy-GPT
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6624
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: QuantizationMethod.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: True
- max_input_length: None
- exllama_config: {'version': <ExllamaVersion.ONE: 1>}
- cache_block_outputs: True
- modules_in_block_to_quantize: None
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.7738 | 0.98 | 31 | 1.4461 |
1.2438 | 1.98 | 63 | 1.2734 |
1.1119 | 2.99 | 95 | 1.1583 |
0.9848 | 4.0 | 127 | 1.0587 |
0.9112 | 4.98 | 158 | 0.9546 |
0.7821 | 5.98 | 190 | 0.8569 |
0.6926 | 6.99 | 222 | 0.7727 |
0.623 | 8.0 | 254 | 0.7120 |
0.5934 | 8.98 | 285 | 0.6737 |
0.5381 | 9.76 | 310 | 0.6624 |
Framework versions
- PEFT 0.5.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.15.2
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Model tree for duneut/healphy-gpt
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ