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/ab2fc8caa89864d9_train_data.json
 model_type: AutoModelForCausalLM
@@ -92,7 +92,7 @@ wandb_name: 1d550d29-f74b-42e2-a40e-b5d8a39cd793
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: 1d550d29-f74b-42e2-a40e-b5d8a39cd793
-warmup_steps: 1
+warmup_steps: 10
 weight_decay: 0.0
 xformers_attention: null
 
@@ -103,6 +103,8 @@ xformers_attention: null
 # 1855e867-21dd-47c5-9e07-776213c95db9
 
 This model is a fine-tuned version of [katuni4ka/tiny-random-falcon-40b](https://huggingface.co/katuni4ka/tiny-random-falcon-40b) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 10.8897
 
 ## Model description
 
@@ -129,14 +131,19 @@ 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        | 0.0014 | 1    | 11.1663         |
+| 44.5734       | 0.0140 | 10   | 11.1312         |
+| 44.2651       | 0.0281 | 20   | 11.0361         |
+| 43.8965       | 0.0421 | 30   | 10.9463         |
+| 43.6562       | 0.0561 | 40   | 10.8998         |
+| 43.5959       | 0.0702 | 50   | 10.8897         |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4eefe3c71f24e802a912ad6036edd184c617e0185b06c83a792606e52cc2b64c
+oid sha256:4fee7708c3a99cf7b365846992ec65c5abf66b01a936d652bf4200c1111defcd
 size 129182