phi-3-5-mini-qlora-output
This model is a fine-tuned version of microsoft/Phi-3.5-mini-instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1575
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.2462 | 0.7319 | 100 | 1.1981 |
1.112 | 1.4639 | 200 | 1.1690 |
1.0515 | 2.1958 | 300 | 1.1615 |
1.1007 | 2.9277 | 400 | 1.1520 |
1.0717 | 3.6597 | 500 | 1.1556 |
1.0474 | 4.3916 | 600 | 1.1575 |
Framework versions
- PEFT 0.13.1
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Model tree for KunalRaghuvanshi/phi-3-5-mini-qlora-output
Base model
microsoft/Phi-3.5-mini-instruct