End of training

README.md

@@ -65,7 +65,7 @@ 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/a85a691963f19b85_train_data.json
 model_type: AutoModelForCausalLM
@@ -90,7 +90,7 @@ wandb_name: a7c81892-f441-469e-9e5c-36ef5a1e8f7f
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: a7c81892-f441-469e-9e5c-36ef5a1e8f7f
-warmup_steps: 10
+warmup_steps: 1
 weight_decay: 0.0
 xformers_attention: null
 
@@ -101,8 +101,6 @@ xformers_attention: null
 # a7c81892-f441-469e-9e5c-36ef5a1e8f7f
 
 This model is a fine-tuned version of [unsloth/Phi-3.5-mini-instruct](https://huggingface.co/unsloth/Phi-3.5-mini-instruct) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: nan
 
 ## Model description
 
@@ -129,19 +127,14 @@ 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        | 0.0005 | 1    | nan             |
-| 0.0           | 0.0055 | 10   | nan             |
-| 0.0           | 0.0110 | 20   | nan             |
-| 0.0           | 0.0165 | 30   | nan             |
-| 0.0           | 0.0219 | 40   | nan             |
-| 0.0           | 0.0274 | 50   | nan             |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1ea59e3f892ff3797c175ab8fb7c462c683c8e5bc0d56cc5e29b30b6b2bf4c82
+oid sha256:7ebaa4950ea2df8ba0c89004747eb71775da3b9ae2e291ed62dca8284e266d54
 size 59930122