TWON-Agents
Collection
4 items
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Updated
TWON-Agent-OSN-Post-de
This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.7415
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.8045 | 1.1173 | 200 | 1.4317 |
| 1.2908 | 2.2346 | 400 | 1.1496 |
| 1.0523 | 3.3520 | 600 | 0.9740 |
| 0.8996 | 4.4693 | 800 | 0.8645 |
| 0.7967 | 5.5866 | 1000 | 0.7943 |
| 0.7339 | 6.7039 | 1200 | 0.7595 |
| 0.6986 | 7.8212 | 1400 | 0.7417 |
Framework versions
- PEFT 0.12.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for simon-muenker/TWON-Agent-OSN-Post-de
Base model
meta-llama/Llama-3.2-3B-Instruct