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/91bf362ff836f818_train_data.json
 model_type: AutoModelForCausalLM
@@ -93,7 +93,7 @@ wandb_name: 8c0ddd56-cdf1-4466-b240-dfcdd2e59fec
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: 8c0ddd56-cdf1-4466-b240-dfcdd2e59fec
-warmup_steps: 1
+warmup_steps: 10
 weight_decay: 0.0
 xformers_attention: null
 
@@ -104,6 +104,8 @@ xformers_attention: null
 # 2b5732f2-c284-4b10-8bb1-1b664fd4d767
 
 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: nan
 
 ## Model description
 
@@ -130,14 +132,19 @@ 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             |
+| 1.632         | 0.0009 | 10   | nan             |
+| 1.2702        | 0.0017 | 20   | nan             |
+| 0.795         | 0.0026 | 30   | nan             |
+| 0.8601        | 0.0034 | 40   | nan             |
+| 0.6914        | 0.0043 | 50   | nan             |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cdb0b8b968a12f2ee8e8ea88e9dfe6977e2d3d8655e5ed27de3098135eb6978f
+oid sha256:17d58bb0fd2bb2acf0d06fddaaa98fe81d1d3987f604c98d2d74bf8733aecf9b
 size 50982842