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/c33a0a3ff4f8ce45_train_data.json
 model_type: AutoModelForCausalLM
@@ -92,7 +92,7 @@ wandb_name: a2fca319-cf34-40c9-8694-ee6777b43d70
 wandb_project: Gradients-On-Demand
 wandb_run: your_name
 wandb_runid: a2fca319-cf34-40c9-8694-ee6777b43d70
-warmup_steps: 1
+warmup_steps: 10
 weight_decay: 0.0
 xformers_attention: null
 
@@ -103,6 +103,8 @@ xformers_attention: null
 # 092ba733-6a48-c324-daf4-74b9b0117cfb
 
 This model is a fine-tuned version of [DeepMount00/Llama-3-8b-Ita](https://huggingface.co/DeepMount00/Llama-3-8b-Ita) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0136
 
 ## 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        | 0.0001 | 1    | 18.5720         |
+| 17.7677       | 0.0006 | 10   | 15.3938         |
+| 3.5892        | 0.0011 | 20   | 1.6451          |
+| 1.1151        | 0.0017 | 30   | 1.0435          |
+| 0.8955        | 0.0023 | 40   | 1.0277          |
+| 0.9464        | 0.0028 | 50   | 1.0136          |
 
 
 ### Framework versions

adapter_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:25e1e5a8593668d3563dbfbfddf725fdacb951666e4c1a3a1e0a3e2ccdefe988
+oid sha256:b781f6741c505fd856c616e9cfa65be762b8695793f7d2650941a5cbd02f8cb2
 size 84047370