Update README.md

README.md

@@ -5,17 +5,53 @@ base_model: Qwen/Qwen2.5-0.5B-Instruct
 tags:
 - generated_from_trainer
 - axolotl
-model-index:
-- name: outputs/qwen05B
-  results: []
 language:
 - it
 - en
 pipeline_tag: text-generation
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+# Qwen2.5-0.5B-Instruct-ITA
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) on the [ReDiX/DataForge](https://huggingface.co/datasets/ReDiX/DataForge) dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4100
+
+## Model description
+
+This model is an example of finetuning a sLLM. Italian eval improved and the model learned as espected from the training data
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+
+|   Tasks    |Version|Filter|n-shot| Metric |   |Value |   |Stderr|
+|------------|------:|------|-----:|--------|---|-----:|---|-----:|
+|arc_it      |      2|none  |     0|acc     |↑  |0.2378|±  |0.0125|
+|            |       |none  |     0|acc_norm|↑  |0.2823|±  |0.0132|
+|hellaswag_it|      1|none  |     0|acc     |↑  |0.3163|±  |0.0049|
+|            |       |none  |     0|acc_norm|↑  |0.3800|±  |0.0051|
+|m_mmlu_it   |      0|none  |     5|acc     |↑  |0.381 |±  |0.0042|
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Use adamw_bnb_8bit 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: 10
+- num_epochs: 2
+
 
 [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
 <details><summary>See axolotl config</summary>
@@ -149,46 +185,6 @@ special_tokens:
 
 </details><br>
 
-# outputs/qwen05B
-
-This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) on the [ReDiX/DataForge](https://huggingface.co/datasets/ReDiX/DataForge) dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.4100
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-
-|   Tasks    |Version|Filter|n-shot| Metric |   |Value |   |Stderr|
-|------------|------:|------|-----:|--------|---|-----:|---|-----:|
-|arc_it      |      2|none  |     0|acc     |↑  |0.2378|±  |0.0125|
-|            |       |none  |     0|acc_norm|↑  |0.2823|±  |0.0132|
-|hellaswag_it|      1|none  |     0|acc     |↑  |0.3163|±  |0.0049|
-|            |       |none  |     0|acc_norm|↑  |0.3800|±  |0.0051|
-|m_mmlu_it   |      0|none  |     5|acc     |↑  |0.381 |±  |0.0042|
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 0.0001
-- train_batch_size: 4
-- eval_batch_size: 4
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 16
-- optimizer: Use adamw_bnb_8bit 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: 10
-- num_epochs: 2
 
 ### Training results