metadata
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: []
image-description_to_emotion
This model is a fine-tuned version of 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