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Model: ReDiX/SmolLM2-360M-Instruct-ita Source: Original Platform
2026-07-08 11:57:11 +08:00
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+---
+library_name: transformers
+license: apache-2.0
+base_model: HuggingFaceTB/SmolLM2-360M
+tags:
+- generated_from_trainer
+- axolotl
+datasets:
+- ReDiX/everyday-conversations-ita
+- ReDiX/DataForge
+language:
+- it
+- en
+pipeline_tag: text-generation
+---
+
+[<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>
+
+axolotl version: `0.5.0`
+```yaml
+base_model: HuggingFaceTB/SmolLM2-360M
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: ./dataforge
+    type: chat_template
+
+    field_messages: conversations
+    message_field_role: from
+    message_field_content: value
+  
+  - path: HuggingFaceTB/smol-smoltalk
+    type: chat_template
+
+    field_messages: messages
+    message_field_role: role
+    message_field_content: content
+
+chat_template: chatml
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.1
+output_dir: ./outputs/smollm360m
+
+sequence_len: 8192
+sample_packing: true
+eval_sample_packing: true
+pad_to_sequence_len: true
+
+wandb_project: axolotl
+wandb_entity:
+wandb_watch:
+wandb_name: smollm2
+wandb_log_model:
+
+gradient_accumulation_steps: 4
+micro_batch_size: 4
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 1.0e-03
+
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16: 
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 5
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 10
+evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+  pad_token: "<|im_end|>"
+  eos_token: "<|im_end|>"
+```
+
+</details><br>
+
+# SmolLM2 360M Instruct ITA
+
+This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-360M](https://huggingface.co/HuggingFaceTB/SmolLM2-360M) on the [smol-smoltalk](https://huggingface.co/datasets/HuggingFaceTB/smol-smoltalk) dataset and on the [ReDiX/DataForge](https://huggingface.co/datasets/ReDiX/DataForge).
+Our datasets is a mixture of open source italian datasets and [ReDiX/everyday-conversations-ita](https://huggingface.co/datasets/ReDiX/everyday-conversations-ita)
+It achieves the following results on the evaluation set:
+- Loss: 0.8925
+
+## Model description
+
+This model is an experiment to test out the [ReDiX/everyday-conversations-ita](https://huggingface.co/datasets/ReDiX/everyday-conversations-ita) dataset.
+
+## Intended uses & limitations
+
+Simple and very basic chat in italian and english
+
+## Training and evaluation data
+
+| Model  |  m_mmlu_it | arc_it  | hellaswag_it  |
+|:------:|:----------:|:-------:|:-------------:|
+| Qwen2.5-0.5-Instruct | **37.05** | 27.54 | 35.73 |
+| ReDiX/SmolLM2-360M-Instruct-ita | 24.94 | **28.40** | **35.96** |
+
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.001
+- 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
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| No log        | 0.0003 | 1    | 1.3366          |
+| 1.0595        | 0.2501 | 774  | 1.0840          |
+| 1.0194        | 0.5002 | 1548 | 1.0139          |
+| 1.0075        | 0.7504 | 2322 | 0.9701          |
+| 1.0286        | 1.0005 | 3096 | 0.9269          |
+| 0.7871        | 1.2506 | 3870 | 0.9111          |
+| 0.7481        | 1.5007 | 4644 | 0.8960          |
+| 0.7429        | 1.7508 | 5418 | 0.8925          |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.20.3