---
library_name: transformers
license: apache-2.0
base_model: HuggingFaceTB/SmolLM2-360M
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: SmolLM2-360M-TemporalQuestions
  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. -->

# SmolLM2-360M-TemporalQuestions

This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-360M](https://huggingface.co/HuggingFaceTB/SmolLM2-360M) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0257
- F1: 0.9846

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 1024
- total_eval_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss | F1     |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.086         | 1.0     | 223  | 0.0629          | 0.9514 |
| 0.1263        | 2.0     | 446  | 0.0466          | 0.9647 |
| 0.0172        | 3.0     | 669  | 0.0351          | 0.9745 |
| 0.0729        | 4.0     | 892  | 0.0319          | 0.9770 |
| 0.0254        | 5.0     | 1115 | 0.0320          | 0.9788 |
| 0.0258        | 6.0     | 1338 | 0.0288          | 0.9798 |
| 0.017         | 7.0     | 1561 | 0.0302          | 0.9812 |
| 0.0278        | 8.0     | 1784 | 0.0302          | 0.9807 |
| 0.0105        | 9.0     | 2007 | 0.0338          | 0.9797 |
| 0.0503        | 10.0    | 2230 | 0.0297          | 0.9808 |
| 0.0148        | 11.0    | 2453 | 0.0257          | 0.9846 |
| 0.0005        | 12.0    | 2676 | 0.0305          | 0.9822 |
| 0.0052        | 13.0    | 2899 | 0.0282          | 0.9853 |
| 0.0012        | 14.0    | 3122 | 0.0317          | 0.9837 |
| 0.0095        | 15.0    | 3345 | 0.0338          | 0.9859 |
| 0.0004        | 16.0    | 3568 | 0.0307          | 0.9865 |
| 0.0003        | 17.0    | 3791 | 0.0336          | 0.9856 |
| 0.0074        | 18.0    | 4014 | 0.0338          | 0.9855 |
| 0.0003        | 19.0    | 4237 | 0.0327          | 0.9864 |
| 0.0003        | 20.0    | 4460 | 0.0353          | 0.9858 |
| 0.0001        | 21.0    | 4683 | 0.0377          | 0.9858 |
| 0.0001        | 22.0    | 4906 | 0.0380          | 0.9870 |
| 0.0001        | 23.0    | 5129 | 0.0389          | 0.9866 |
| 0.0001        | 24.0    | 5352 | 0.0399          | 0.9866 |
| 0.0001        | 25.0    | 5575 | 0.0404          | 0.9866 |
| 0.0001        | 26.0    | 5798 | 0.0408          | 0.9867 |
| 0.0001        | 27.0    | 6021 | 0.0409          | 0.9867 |
| 0.0002        | 28.0    | 6244 | 0.0411          | 0.9867 |
| 0.0001        | 29.0    | 6467 | 0.0411          | 0.9867 |
| 0.0023        | 29.8691 | 6660 | 0.0412          | 0.9867 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.0.1
- Tokenizers 0.21.0