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: 1
+max_steps: 50
 micro_batch_size: 2
 mlflow_experiment_name: /tmp/93487c1592616e24_train_data.json
 model_type: AutoModelForCausalLM
@@ -91,7 +91,7 @@ wandb_name: d9e2189f-0b5f-45ba-8f13-516ece5d38df
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: d9e2189f-0b5f-45ba-8f13-516ece5d38df
-warmup_steps: 1
+warmup_steps: 10
 weight_decay: 0.0
 xformers_attention: null
 
@@ -102,6 +102,8 @@ xformers_attention: null
 # 13438d57-e926-1cb6-033c-9d9ac7c07a88
 
 This model is a fine-tuned version of [unsloth/Llama-3.1-Storm-8B](https://huggingface.co/unsloth/Llama-3.1-Storm-8B) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: nan
 
 ## Model description
 
@@ -128,14 +130,19 @@ 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: 2
-- training_steps: 1
+- lr_scheduler_warmup_steps: 10
+- training_steps: 50
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss |
 |:-------------:|:------:|:----:|:---------------:|
 | No log        | 0.0001 | 1    | nan             |
+| 3.815         | 0.0006 | 10   | nan             |
+| 1.5347        | 0.0011 | 20   | nan             |
+| 0.6934        | 0.0017 | 30   | nan             |
+| 0.2649        | 0.0023 | 40   | nan             |
+| 0.2735        | 0.0029 | 50   | nan             |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e3b666a393e7bdefd5de2ab50b006e28ded5b9606d006a2404f825def8c5f516
+oid sha256:3fb134130224ea0b1753787cac553b2275f5082619c5febeb7d8d7a586181af1
 size 84047370