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: 1
+max_steps: 50
 micro_batch_size: 2
 mlflow_experiment_name: /tmp/afc0e3928189719b_train_data.json
 model_type: AutoModelForCausalLM
@@ -90,7 +90,7 @@ wandb_name: 530c2501-068b-462a-8f6d-255379e8db0e
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: 530c2501-068b-462a-8f6d-255379e8db0e
-warmup_steps: 1
+warmup_steps: 10
 weight_decay: 0.0
 xformers_attention: null
 
@@ -101,6 +101,8 @@ xformers_attention: null
 # 530c2501-068b-462a-8f6d-255379e8db0e
 
 This model is a fine-tuned version of [unsloth/Llama-3.2-1B](https://huggingface.co/unsloth/Llama-3.2-1B) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0000
 
 ## Model description
 
@@ -127,14 +129,19 @@ 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        | 0.0005 | 1    | 10.1790         |
+| 7.4845        | 0.0053 | 10   | 3.2548          |
+| 0.0006        | 0.0105 | 20   | 0.0003          |
+| 0.0           | 0.0158 | 30   | 0.0000          |
+| 0.0           | 0.0211 | 40   | 0.0000          |
+| 0.0           | 0.0263 | 50   | 0.0000          |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ea029da8b636911e4b14242adc1c3ae872bb817abf53f1f1f4fa0d3de010c803
+oid sha256:9943a74d24c302de64af71af4f7be2c12ff99e63efe8f7e1cb6811b940c2b87d
 size 22624970