Model save

README.md

@@ -4,19 +4,18 @@ license: apache-2.0
 base_model: Qwen/Qwen2.5-7B-Instruct
 tags:
 - llama-factory
-- full
 - generated_from_trainer
 model-index:
-- name: fig1_all_s1
+- name: s1
   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. -->
 
-# fig1_all_s1
+# s1
 
-This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the mlfoundations-dev/fig1_all_s1 dataset.
+This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on an unknown dataset.
 
 ## Model description
 
@@ -40,11 +39,11 @@ The following hyperparameters were used during training:
 - eval_batch_size: 8
 - seed: 42
 - distributed_type: multi-GPU
-- num_devices: 8
-- gradient_accumulation_steps: 12
+- num_devices: 4
+- gradient_accumulation_steps: 24
 - total_train_batch_size: 96
-- total_eval_batch_size: 64
-- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- total_eval_batch_size: 32
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: cosine
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 7.0
@@ -56,6 +55,6 @@ The following hyperparameters were used during training:
 ### Framework versions
 
 - Transformers 4.46.1
-- Pytorch 2.3.0
+- Pytorch 2.6.0+cu124
 - Datasets 3.1.0
 - Tokenizers 0.20.3