End of training

README.md

@@ -1,8 +1,9 @@
 ---
 license: apache-2.0
-base_model: TheBloke/Mistral-7B-Instruct-v0.1-GPTQ
+library_name: peft
 tags:
 - generated_from_trainer
+base_model: TheBloke/Mistral-7B-Instruct-v0.1-GPTQ
 model-index:
 - name: mistral-finetuned-samsum
   results: []
@@ -29,6 +30,28 @@ 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:
@@ -38,7 +61,7 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
-- training_steps: 250
+- training_steps: 50
 - mixed_precision_training: Native AMP
 
 ### Training results
@@ -47,7 +70,8 @@ The following hyperparameters were used during training:
 
 ### Framework versions
 
-- Transformers 4.35.0.dev0
-- Pytorch 2.0.1+cu118
-- Datasets 2.14.5
-- Tokenizers 0.14.1
+- PEFT 0.7.0
+- Transformers 4.36.0.dev0
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0