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/d5f326b7c109b091_train_data.json
 model_type: AutoModelForCausalLM
@@ -90,7 +90,7 @@ wandb_name: 7e28d9c5-d916-41c7-aa4a-dff1eedab09c
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: 7e28d9c5-d916-41c7-aa4a-dff1eedab09c
-warmup_steps: 1
+warmup_steps: 10
 weight_decay: 0.0
 xformers_attention: null
 
@@ -101,6 +101,8 @@ xformers_attention: null
 # bfc08a13-1daa-5df3-61c7-6979f7ea7e3b
 
 This model is a fine-tuned version of [unsloth/tinyllama-chat](https://huggingface.co/unsloth/tinyllama-chat) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2173
 
 ## 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        | 0.0002 | 1    | 3.3472          |
+| 3.1632        | 0.0020 | 10   | 2.9211          |
+| 2.1787        | 0.0041 | 20   | 1.8444          |
+| 1.3913        | 0.0061 | 30   | 1.3631          |
+| 1.2526        | 0.0081 | 40   | 1.2399          |
+| 1.2177        | 0.0101 | 50   | 1.2173          |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d39de68ae36e3db908985c209acd52e3f653a9a8f74a72bef901e0a349e5aa19
+oid sha256:182bcbc24a796651893e2e63e2806ddfcd4c5f953c2f48ed2f413aabab2dfc13
 size 25342042