Best model at step 0 with eval_loss=1.6147 | WandB Run: https://wandb.ai/tuandung/Qwen2.5-Coder-1.5B-Instruct-LoRA-Training/runs/62a2gru6

README.md

@@ -17,10 +17,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [unsloth/qwen2.5-coder-1.5b-instruct-bnb-4bit](https://huggingface.co/unsloth/qwen2.5-coder-1.5b-instruct-bnb-4bit) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 1.6159
-- eval_runtime: 32.7693
-- eval_samples_per_second: 3.662
-- eval_steps_per_second: 0.458
+- eval_loss: 1.6147
+- eval_runtime: 25.1219
+- eval_samples_per_second: 3.583
+- eval_steps_per_second: 0.478
 - epoch: 0
 - step: 0
 
@@ -42,15 +42,15 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 12
+- train_batch_size: 20
 - eval_batch_size: 8
 - seed: 42
 - gradient_accumulation_steps: 2
-- total_train_batch_size: 24
+- total_train_batch_size: 40
 - optimizer: Use lion_8bit and the args are:
 No additional optimizer arguments
 - lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 42
+- lr_scheduler_warmup_steps: 25
 - num_epochs: 3
 - mixed_precision_training: Native AMP
 

training_args.bin

@@ -1,3 +1,3 @@
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 size 5560