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/649bdfca538c70bf_train_data.json
 model_type: AutoModelForCausalLM
@@ -93,7 +93,7 @@ wandb_name: 07f8d1d8-e3f2-4ae9-85d6-990c68403f80
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: 07f8d1d8-e3f2-4ae9-85d6-990c68403f80
-warmup_steps: 1
+warmup_steps: 10
 weight_decay: 0.0
 xformers_attention: null
 
@@ -104,6 +104,8 @@ xformers_attention: null
 # 07f8d1d8-e3f2-4ae9-85d6-990c68403f80
 
 This model is a fine-tuned version of [echarlaix/tiny-random-PhiForCausalLM](https://huggingface.co/echarlaix/tiny-random-PhiForCausalLM) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 6.9103
 
 ## Model description
 
@@ -130,14 +132,19 @@ 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    | 6.9276          |
+| No log        | 0.0008 | 1    | 6.9277          |
+| 6.9263        | 0.0077 | 10   | 6.9248          |
+| 6.9265        | 0.0154 | 20   | 6.9185          |
+| 6.9186        | 0.0231 | 30   | 6.9134          |
+| 6.9174        | 0.0308 | 40   | 6.9107          |
+| 6.9151        | 0.0385 | 50   | 6.9103          |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:19b8385a6dfab3d71a935e1793f7102c80df75deb622c2f7f4c0206bd0e4187a
+oid sha256:74ce539e58d6e44db57717f509d8c357a68159ace5861124384029a10af4ea94
 size 168063