---
library_name: transformers
license: apache-2.0
base_model: Trelis/SmolLM-135M-Instruct-layer-pruned-90M-raw
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: 99-v9
  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. -->

# 99-v9

This model is a fine-tuned version of [Trelis/SmolLM-135M-Instruct-layer-pruned-90M-raw](https://huggingface.co/Trelis/SmolLM-135M-Instruct-layer-pruned-90M-raw) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7495

## 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: 0.002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.005
- lr_scheduler_warmup_steps: 89
- training_steps: 17894

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.6331        | 0.0500 | 894   | 0.6004          |
| 0.5667        | 0.0999 | 1788  | 0.5463          |
| 0.5423        | 0.1499 | 2682  | 0.5138          |
| 0.5749        | 0.1998 | 3576  | 0.7377          |
| 0.5378        | 0.2498 | 4470  | 0.7542          |
| 0.506         | 0.2998 | 5364  | 0.7902          |
| 0.5561        | 0.3497 | 6258  | 0.7810          |
| 0.5259        | 0.3997 | 7152  | 0.7914          |
| 0.5516        | 0.4496 | 8046  | 0.7611          |
| 0.5131        | 0.4996 | 8940  | 0.6860          |
| 0.5069        | 0.5496 | 9834  | 0.7247          |
| 0.4977        | 0.5995 | 10728 | 0.7375          |
| 0.4976        | 0.6495 | 11622 | 0.7436          |
| 0.5018        | 0.6995 | 12516 | 0.7520          |
| 0.537         | 0.7494 | 13410 | 0.7613          |
| 0.5018        | 0.7994 | 14304 | 0.6922          |
| 0.4891        | 0.8493 | 15198 | 0.7322          |
| 0.4808        | 0.8993 | 16092 | 0.7430          |
| 0.5231        | 0.9493 | 16986 | 0.7546          |
| 0.5103        | 0.9992 | 17880 | 0.7495          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1