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: 8
 mlflow_experiment_name: /tmp/69ffe4b4886a75f3_train_data.json
 model_type: AutoModelForCausalLM
@@ -93,7 +93,7 @@ wandb_name: 44c9e4b4-5d69-4903-b23a-8a53dfad8e10
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: 44c9e4b4-5d69-4903-b23a-8a53dfad8e10
-warmup_steps: 1
+warmup_steps: 2
 weight_decay: 0.0
 xformers_attention: null
 
@@ -104,6 +104,8 @@ xformers_attention: null
 # 44c9e4b4-5d69-4903-b23a-8a53dfad8e10
 
 This model is a fine-tuned version of [heegyu/WizardVicuna-open-llama-3b-v2](https://huggingface.co/heegyu/WizardVicuna-open-llama-3b-v2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3192
 
 ## Model description
 
@@ -131,13 +133,17 @@ The following hyperparameters were used during training:
 - 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
+- training_steps: 34
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss |
 |:-------------:|:------:|:----:|:---------------:|
 | No log        | 0.0296 | 1    | 3.7178          |
+| No log        | 0.2070 | 7    | 2.2528          |
+| 2.8926        | 0.4140 | 14   | 1.6521          |
+| 1.6732        | 0.6211 | 21   | 1.4499          |
+| 1.6732        | 0.8281 | 28   | 1.3192          |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c10ae1d7506038b3f51af2dd0ae2f827334fc578c5b0e3dc6e4127cdf8394cbf
+oid sha256:fcb5c47b238dc03e401c65281db78e83dcbe6a2155d56f604af4e192ef611bbe
 size 50982842