CodePhi-3-mini-128k-instruct-St
This model is a fine-tuned version of microsoft/Phi-3-mini-128k-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8475
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-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 450
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.7314 | 0.1111 | 50 | 1.0823 |
0.6329 | 0.2222 | 100 | 0.9492 |
0.4915 | 0.3333 | 150 | 0.8924 |
0.4442 | 0.4444 | 200 | 0.8674 |
0.4184 | 0.5556 | 250 | 0.8540 |
0.4269 | 0.6667 | 300 | 0.8491 |
0.3887 | 0.7778 | 350 | 0.8483 |
0.3898 | 0.8889 | 400 | 0.8480 |
0.3992 | 1.0 | 450 | 0.8475 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Downloads last month
- 135
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for AdnanRiaz107/CodePhi-3-mini-128k-instruct-St
Base model
microsoft/Phi-3-mini-128k-instruct