---
library_name: peft
license: apache-2.0
base_model: HuggingFaceTB/SmolLM2-135M-Instruct
tags:
- generated_from_trainer
model-index:
- name: SmolLM2-135M-Instruct-Arabic-test
  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. -->

# SmolLM2-135M-Instruct-Arabic-test

This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2311

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.PAGED_ADAMW with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.6658        | 0.0889 | 100  | 1.6589          |
| 1.6393        | 0.1778 | 200  | 1.5819          |
| 1.5377        | 0.2667 | 300  | 1.5419          |
| 1.5329        | 0.3556 | 400  | 1.5107          |
| 1.4348        | 0.4444 | 500  | 1.4799          |
| 1.4884        | 0.5333 | 600  | 1.4576          |
| 1.3968        | 0.6222 | 700  | 1.4366          |
| 1.432         | 0.7111 | 800  | 1.4194          |
| 1.4154        | 0.8    | 900  | 1.4033          |
| 1.3925        | 0.8889 | 1000 | 1.3879          |
| 1.4315        | 0.9778 | 1100 | 1.3771          |
| 1.3474        | 1.0667 | 1200 | 1.3649          |
| 1.3419        | 1.1556 | 1300 | 1.3524          |
| 1.358         | 1.2444 | 1400 | 1.3450          |
| 1.3034        | 1.3333 | 1500 | 1.3356          |
| 1.2675        | 1.4222 | 1600 | 1.3258          |
| 1.3282        | 1.5111 | 1700 | 1.3186          |
| 1.2946        | 1.6    | 1800 | 1.3098          |
| 1.2936        | 1.6889 | 1900 | 1.3027          |
| 1.2275        | 1.7778 | 2000 | 1.2956          |
| 1.2438        | 1.8667 | 2100 | 1.2915          |
| 1.2819        | 1.9556 | 2200 | 1.2826          |
| 1.2551        | 2.0444 | 2300 | 1.2767          |
| 1.2067        | 2.1333 | 2400 | 1.2799          |
| 1.2313        | 2.2222 | 2500 | 1.2687          |
| 1.2186        | 2.3111 | 2600 | 1.2633          |
| 1.2393        | 2.4    | 2700 | 1.2587          |
| 1.1746        | 2.4889 | 2800 | 1.2507          |
| 1.2061        | 2.5778 | 2900 | 1.2494          |
| 1.2453        | 2.6667 | 3000 | 1.2434          |
| 1.1822        | 2.7556 | 3100 | 1.2414          |
| 1.1563        | 2.8444 | 3200 | 1.2335          |
| 1.173         | 2.9333 | 3300 | 1.2311          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.51.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0