logs
This model is a fine-tuned version of microsoft/Phi-3-mini-128k-instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2743
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: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.0529 | 0.9956 | 112 | 1.1079 |
0.8563 | 2.0 | 225 | 1.0902 |
0.684 | 2.9956 | 337 | 1.1762 |
0.5762 | 3.9822 | 448 | 1.2743 |
Framework versions
- PEFT 0.11.1
- Transformers 4.40.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for akshatshaw/logs
Base model
microsoft/Phi-3-mini-128k-instruct