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: 8
 mlflow_experiment_name: /tmp/3ba5b972fa0124d3_train_data.json
 model_type: AutoModelForCausalLM
@@ -90,7 +90,7 @@ wandb_name: ec7ab51c-de79-4f21-889e-2f6eba75a8e2
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: ec7ab51c-de79-4f21-889e-2f6eba75a8e2
-warmup_steps: 1
+warmup_steps: 2
 weight_decay: 0.0
 xformers_attention: null
 
@@ -101,6 +101,8 @@ xformers_attention: null
 # ec7ab51c-de79-4f21-889e-2f6eba75a8e2
 
 This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.1146
 
 ## Model description
 
@@ -128,13 +130,18 @@ 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: 50
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss |
 |:-------------:|:------:|:----:|:---------------:|
 | No log        | 0.0058 | 1    | 2.3134          |
+| 2.2689        | 0.0579 | 10   | 2.2091          |
+| 2.1851        | 0.1159 | 20   | 2.1506          |
+| 2.1462        | 0.1738 | 30   | 2.1253          |
+| 2.1183        | 0.2317 | 40   | 2.1161          |
+| 2.127         | 0.2896 | 50   | 2.1146          |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:45e1dfe0cd5ff516b793daa1cd926a1f7c4ea0e2a8adadaa46e5f3b8ea4f6c0a
+oid sha256:e4453ee3fda954d6be8f48318c65689b07edc0495221ad4da04bc64211d0a7b4
 size 17717130