Model save

README.md

@@ -1,22 +1,22 @@
 ---
-license: llama3
+base_model: meta-llama/Llama-3.2-1B-Instruct
 library_name: peft
+license: llama3.2
 tags:
 - trl
 - sft
 - generated_from_trainer
-base_model: meta-llama/Meta-Llama-3-8B
 model-index:
-- name: llama3-8b-sft-qlora-re-FT_filter
+- name: llama3.2-8b-sft-qlora-re-FT_filter
   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. -->
 
-# llama3-8b-sft-qlora-re-FT_filter
+# llama3.2-8b-sft-qlora-re-FT_filter
 
-This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on an unknown dataset.
+This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) on an unknown dataset.
 
 ## Model description
 
@@ -39,7 +39,7 @@ The following hyperparameters were used during training:
 - train_batch_size: 4
 - eval_batch_size: 8
 - seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- optimizer: Use adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: constant
 - lr_scheduler_warmup_ratio: 0.03
 - num_epochs: 2
@@ -51,8 +51,8 @@ The following hyperparameters were used during training:
 
 ### Framework versions
 
-- PEFT 0.11.1
-- Transformers 4.41.2
-- Pytorch 2.3.0+cu121
-- Datasets 2.20.0
-- Tokenizers 0.19.1
+- PEFT 0.13.2
+- Transformers 4.46.0
+- Pytorch 2.5.0+cu121
+- Datasets 3.0.2
+- Tokenizers 0.20.1