fine-tuned_phi3.5
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: 1.2392
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: 6
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- training_steps: 100
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0.0244 | 10 | 1.4131 |
No log | 0.0487 | 20 | 1.3193 |
1.4022 | 0.0731 | 30 | 1.2778 |
1.4022 | 0.0975 | 40 | 1.2651 |
1.2145 | 0.1219 | 50 | 1.2546 |
1.2145 | 0.1462 | 60 | 1.2479 |
1.2145 | 0.1706 | 70 | 1.2449 |
1.1869 | 0.1950 | 80 | 1.2413 |
1.1869 | 0.2193 | 90 | 1.2402 |
1.2108 | 0.2437 | 100 | 1.2392 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.0.0+nv23.05
- Datasets 2.15.0
- Tokenizers 0.19.1
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Model tree for kshitij1188/fine-tuned_phi3.5
Base model
microsoft/Phi-3.5-mini-instruct