End of training

README.md

@@ -66,7 +66,7 @@ lora_model_dir: null
 lora_r: 8
 lora_target_linear: true
 lr_scheduler: cosine
-max_steps: 50
+max_steps: 1
 micro_batch_size: 2
 mlflow_experiment_name: /tmp/8e867e0c95f85985_train_data.json
 model_type: AutoModelForCausalLM
@@ -91,7 +91,7 @@ wandb_name: 3d129001-be65-406a-a409-10f99a17a16f
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: 3d129001-be65-406a-a409-10f99a17a16f
-warmup_steps: 10
+warmup_steps: 1
 weight_decay: 0.0
 xformers_attention: null
 
@@ -102,8 +102,6 @@ xformers_attention: null
 # 3d129001-be65-406a-a409-10f99a17a16f
 
 This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B](https://huggingface.co/Qwen/Qwen2.5-1.5B) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.9800
 
 ## Model description
 
@@ -130,19 +128,14 @@ The following hyperparameters were used during training:
 - total_train_batch_size: 8
 - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 10
-- training_steps: 50
+- lr_scheduler_warmup_steps: 2
+- training_steps: 1
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss |
 |:-------------:|:------:|:----:|:---------------:|
 | No log        | 0.0004 | 1    | 7.8545          |
-| 7.2747        | 0.0043 | 10   | 6.5191          |
-| 3.2579        | 0.0085 | 20   | 3.1600          |
-| 3.3705        | 0.0128 | 30   | 2.4028          |
-| 2.5675        | 0.0170 | 40   | 2.0254          |
-| 1.0902        | 0.0213 | 50   | 1.9800          |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:83b54464d5df3f1d5f7a4e57dd0b7a166ec46ed44f611b61f9b2d2212d264950
 size 37070634