metadata
base_model: microsoft/Phi-3-mini-4k-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: phi-3-text2sql-ssh
results: []
phi-3-text2sql-ssh
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7745
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: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0 | 0 | 2.8774 |
1.3552 | 0.1072 | 500 | 0.8898 |
0.8559 | 0.2143 | 1000 | 0.8311 |
0.8152 | 0.3215 | 1500 | 0.8096 |
0.7986 | 0.4287 | 2000 | 0.7940 |
0.7901 | 0.5358 | 2500 | 0.7866 |
0.7876 | 0.6430 | 3000 | 0.7806 |
0.7806 | 0.7502 | 3500 | 0.7767 |
0.7729 | 0.8574 | 4000 | 0.7751 |
0.7735 | 0.9645 | 4500 | 0.7745 |
Framework versions
- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.2.1+cu121
- Datasets 2.15.0
- Tokenizers 0.19.1