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/ea9bcbda19ac93b0_train_data.json
 model_type: AutoModelForCausalLM
@@ -90,7 +90,7 @@ wandb_name: 94aedb3a-a10c-48eb-92a0-8db309f6f24e
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: 94aedb3a-a10c-48eb-92a0-8db309f6f24e
-warmup_steps: 1
+warmup_steps: 10
 weight_decay: 0.0
 xformers_attention: null
 
@@ -101,6 +101,8 @@ xformers_attention: null
 # 13f84693-d330-3b01-d18b-36c968f891fa
 
 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: 0.5088
 
 ## 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        | 0.0001 | 1    | 2.0436          |
+| 1.82          | 0.0008 | 10   | 1.3071          |
+| 0.7031        | 0.0015 | 20   | 0.6722          |
+| 0.5842        | 0.0023 | 30   | 0.5466          |
+| 0.53          | 0.0030 | 40   | 0.5143          |
+| 0.4892        | 0.0038 | 50   | 0.5088          |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4e409dc22ee6dc2fce778763b8d0738c51677ac34e2aa051312d2b335d82bc27
+oid sha256:81a32d55d97d940d0fcc128be7fafcdc46552ca0b91ceea54f8ff463b4bb16cc
 size 84047370