End of training

README.md

@@ -66,7 +66,7 @@ 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/d0b0bf79b09cfb84_train_data.json
 model_type: AutoModelForCausalLM
@@ -91,7 +91,7 @@ wandb_name: d1b9408a-8b32-42be-94a7-434382605027
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: d1b9408a-8b32-42be-94a7-434382605027
-warmup_steps: 1
+warmup_steps: 10
 weight_decay: 0.0
 xformers_attention: null
 
@@ -102,6 +102,8 @@ xformers_attention: null
 # d1b9408a-8b32-42be-94a7-434382605027
 
 This model is a fine-tuned version of [unsloth/mistral-7b-instruct-v0.3](https://huggingface.co/unsloth/mistral-7b-instruct-v0.3) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2119
 
 ## Model description
 
@@ -128,14 +130,19 @@ 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        | 0.0021 | 1    | 0.8276          |
+| 0.841         | 0.0212 | 10   | 0.2516          |
+| 0.7493        | 0.0423 | 20   | 0.2253          |
+| 1.2061        | 0.0635 | 30   | 0.2232          |
+| 0.5583        | 0.0846 | 40   | 0.2132          |
+| 0.6284        | 0.1058 | 50   | 0.2119          |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:56e4720aa6d43895f20aac40da83b685d0969d8dffeaaa1ac3637db56fed373b
+oid sha256:355328dbd7965440aebde0014a55ab79f5af924a275303e3821bc1f93c092570
 size 84047370