phi3.5-mini-adapter_v0
This model is a fine-tuned version of microsoft/Phi-3.5-mini-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0423
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: 0.0002
- 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: cosine
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 250
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 11.9711 | 0.1509 | 10 | 10.5546 |
| 0.0847 | 0.3019 | 20 | 0.1104 |
| 0.0989 | 0.4528 | 30 | 0.0840 |
| 0.0543 | 0.6038 | 40 | 0.0588 |
| 0.0392 | 0.7547 | 50 | 0.0490 |
| 0.0447 | 0.9057 | 60 | 0.0457 |
| 0.0465 | 1.0566 | 70 | 0.0435 |
| 0.0317 | 1.2075 | 80 | 0.0445 |
| 0.0443 | 1.3585 | 90 | 0.0423 |
Framework versions
- PEFT 0.11.1
- Transformers 4.43.1
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for BTGFM/phi3.5-mini-adapter_v0
Base model
microsoft/Phi-3.5-mini-instruct