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/78b017747938b3c4_train_data.json
 model_type: AutoModelForCausalLM
@@ -90,7 +90,7 @@ wandb_name: deffb62d-23fb-4eeb-bebf-93ee30b6a5ce
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: deffb62d-23fb-4eeb-bebf-93ee30b6a5ce
-warmup_steps: 1
+warmup_steps: 10
 weight_decay: 0.0
 xformers_attention: null
 
@@ -101,6 +101,8 @@ xformers_attention: null
 # 96459ea4-75da-49f2-a74a-cf8a0500a772
 
 This model is a fine-tuned version of [unsloth/mistral-7b-instruct-v0.2](https://huggingface.co/unsloth/mistral-7b-instruct-v0.2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0390
 
 ## 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        | 0.0022 | 1    | 2.5055          |
+| 8.2572        | 0.0220 | 10   | 1.4577          |
+| 4.9255        | 0.0441 | 20   | 1.1569          |
+| 4.2952        | 0.0661 | 30   | 1.0599          |
+| 4.4237        | 0.0881 | 40   | 1.0437          |
+| 4.104         | 0.1101 | 50   | 1.0390          |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e8e34905522747ba0cc1534be07f3c323f0baed53eefb1efdf696fba20dfcc7b
+oid sha256:20ed22dac850030234b5ea6a605c9bcad82c1b64ff882719a8adae1b4213e0d4
 size 84047370