End of training

README.md

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+---
+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: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# mistral-finetuned-samsum
+
+This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.1-GPTQ](https://huggingface.co/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