End of training

README.md

@@ -64,7 +64,7 @@ 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/46e160ef3ae0ab3c_train_data.json
 model_type: AutoModelForCausalLM
@@ -89,7 +89,7 @@ wandb_name: 46f18893-f88b-40e2-a9c8-f78a6bccf61a
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: 46f18893-f88b-40e2-a9c8-f78a6bccf61a
-warmup_steps: 1
+warmup_steps: 10
 weight_decay: 0.0
 xformers_attention: null
 
@@ -100,6 +100,8 @@ xformers_attention: null
 # e25d67d8-c27c-4ef5-83c2-e75e464f73ee
 
 This model is a fine-tuned version of [MNC-Jihun/Mistral-7B-AO-u0.5-b2-ver0.4](https://huggingface.co/MNC-Jihun/Mistral-7B-AO-u0.5-b2-ver0.4) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5841
 
 ## Model description
 
@@ -126,14 +128,19 @@ 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    | 0.9849          |
+| No log        | 0.0001 | 1    | 0.9394          |
+| 0.7874        | 0.0013 | 10   | 0.6841          |
+| 0.6392        | 0.0025 | 20   | 0.6125          |
+| 0.5875        | 0.0038 | 30   | 0.5959          |
+| 0.5706        | 0.0051 | 40   | 0.5859          |
+| 0.5796        | 0.0064 | 50   | 0.5841          |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:2f570e692fcb4e4fd3d5670866cd99aaae0151fc510acef119969e71f6c836f0
 size 608352466