TWON-Agents
Collection
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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: 0.8584
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 |
|---|---|---|---|
| 1.7982 | 1.3245 | 200 | 1.4543 |
| 1.2778 | 2.6490 | 400 | 1.1855 |
| 1.0508 | 3.9735 | 600 | 1.0354 |
| 0.9074 | 5.2980 | 800 | 0.9398 |
| 0.8202 | 6.6225 | 1000 | 0.8805 |
| 0.7794 | 7.9470 | 1200 | 0.8585 |
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