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---
license: apache-2.0
base_model: HuggingFaceTB/SmolLM-360M
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceTB/everyday-topics-MT-conversations-H4
- HuggingFaceTB/instruct-data-basics-H4
model-index:
- name: smollm-350M-instruct-add-basics-only
results: []
---
<!-- 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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/loubnabnl/huggingface/runs/6sdxeci4)
# smollm-350M-instruct-add-basics-only
This model is a fine-tuned version of [HuggingFaceTB/SmolLM-360M](https://huggingface.co/HuggingFaceTB/SmolLM-360M) on the HuggingFaceTB/everyday-topics-MT-conversations-H4 and the HuggingFaceTB/instruct-data-basics-H4 datasets.
It achieves the following results on the evaluation set:
- Loss: 1.4730
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## 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
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.2577 | 0.5714 | 1 | 2.2421 |
| 2.2317 | 1.7143 | 3 | 2.2371 |
| 2.8729 | 2.8571 | 5 | 1.4730 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
|