SmolVLM-500M-Instruct-fer0

Fine-tuned version of SmolVLM-500M-Instruct on a subset of AffectNet (emotion recognition), with text labels transcribed via GPT-4o-mini.

This is just priliminary, we'll update soon with proper evalutation and info.

Example

Image input

Predictions:

• Base model: A woman with blonde hair is looking to the side with a hand on her chin.
• This model: The expression conveys a sense of contemplation or concern. The furrowed brow and slightly parted lips suggest a deep thought or worry. The hand on the chin indicates a hint of introspection, hinting at a possible emotional state of unease or contemplation.

Training Summary

• Loss values:

Step	Training Loss
25	2.80
50	0.82
75	0.48
100	0.43

• Hyperparameters:
  • Learning rate: 1e-4
  • Batch size: 4 (grad. accum. ×4)
  • Epochs: 1
  • Optimizer: 8-bit AdamW
  • Scheduler: linear (warmup 50 steps)
  • Seed: 42

Frameworks

• Transformers 4.50.0
• PyTorch 2.3.1+cu121
• Datasets 3.6.0
• Tokenizers 0.21.1