---
library_name: transformers
license: apache-2.0
base_model: HuggingFaceTB/SmolLM2-135M
tags:
- smol-course
- module_1
- trl
- sft
- generated_from_trainer
model-index:
- name: SmolLM2-FT
  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. -->

# SmolLM2-FT

This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M](https://huggingface.co/HuggingFaceTB/SmolLM2-135M) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0016

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0523        | 0.0885 | 50   | 1.1397          |
| 1.096         | 0.1770 | 100  | 1.1030          |
| 1.048         | 0.2655 | 150  | 1.0750          |
| 1.0342        | 0.3540 | 200  | 1.0596          |
| 1.0262        | 0.4425 | 250  | 1.0505          |
| 1.0168        | 0.5310 | 300  | 1.0413          |
| 0.989         | 0.6195 | 350  | 1.0342          |
| 0.992         | 0.7080 | 400  | 1.0307          |
| 1.0056        | 0.7965 | 450  | 1.0224          |
| 1.0605        | 0.8850 | 500  | 1.0137          |
| 0.9758        | 0.9735 | 550  | 1.0081          |
| 0.7922        | 1.0619 | 600  | 1.0134          |
| 0.8005        | 1.1504 | 650  | 1.0096          |
| 0.7443        | 1.2389 | 700  | 1.0111          |
| 0.8439        | 1.3274 | 750  | 1.0089          |
| 0.8013        | 1.4159 | 800  | 1.0050          |
| 0.7648        | 1.5044 | 850  | 1.0054          |
| 0.8123        | 1.5929 | 900  | 1.0030          |
| 0.8511        | 1.6814 | 950  | 1.0018          |
| 0.7797        | 1.7699 | 1000 | 1.0016          |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu118
- Datasets 3.0.2
- Tokenizers 0.20.0