End of training

README.md

@@ -1,28 +1,52 @@
 ---
-library_name: peft
+license: apache-2.0
+base_model: TheBloke/Mistral-7B-Instruct-v0.1-GPTQ
+tags:
+- generated_from_trainer
+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
 
+### Training hyperparameters
 
-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
-- disable_exllama: True
-- max_input_length: None
-### Framework versions
+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
+
+### Training results
 
 
-- PEFT 0.5.0
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1