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/71d460e8fe369638_train_data.json
 model_type: AutoModelForCausalLM
@@ -90,7 +90,7 @@ wandb_name: 9d4a8483-6ce6-4fe5-90dd-8a6614e2d453
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: 9d4a8483-6ce6-4fe5-90dd-8a6614e2d453
-warmup_steps: 1
+warmup_steps: 10
 weight_decay: 0.0
 xformers_attention: null
 
@@ -101,6 +101,8 @@ xformers_attention: null
 # af285ff4-c02f-8b6f-9a18-9aad016c5825
 
 This model is a fine-tuned version of [unsloth/Meta-Llama-3.1-8B](https://huggingface.co/unsloth/Meta-Llama-3.1-8B) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2831
 
 ## 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        | 0.0008 | 1    | 1.3235          |
+| 0.7889        | 0.0076 | 10   | 0.8517          |
+| 0.406         | 0.0152 | 20   | 0.4668          |
+| 0.1856        | 0.0228 | 30   | 0.3168          |
+| 0.2666        | 0.0304 | 40   | 0.2875          |
+| 0.2762        | 0.0380 | 50   | 0.2831          |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1ba5decb9a69f4a5aa0cd83f6c0e8c3674efbc8e4dcf021c9bf8a382ceb0dc64
+oid sha256:95d5ab63087e122069e50ef3a8f8f8ab796b1864b197d036b0de03fa1e9df4ff
 size 84047370