---
base_model: HuggingFaceTB/SmolLM2-360M
datasets:
- arrow
library_name: transformers
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: image-description_to_emotion
  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. -->

# image-description_to_emotion

This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-360M](https://huggingface.co/HuggingFaceTB/SmolLM2-360M) on the arrow dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1650

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5979        | 0.3361 | 50   | 0.5039          |
| 0.3262        | 0.6723 | 100  | 0.2783          |
| 0.2599        | 1.0084 | 150  | 0.2305          |
| 0.2211        | 1.3445 | 200  | 0.2071          |
| 0.2004        | 1.6807 | 250  | 0.1969          |
| 0.2094        | 2.0168 | 300  | 0.1840          |
| 0.1788        | 2.3529 | 350  | 0.1797          |
| 0.1709        | 2.6891 | 400  | 0.1739          |
| 0.1604        | 3.0252 | 450  | 0.1693          |
| 0.141         | 3.3613 | 500  | 0.1671          |
| 0.1479        | 3.6975 | 550  | 0.1650          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1