metadata
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Phi-3.5-MultiCap
results: []
Phi-3.5-MultiCap
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: 0.5367
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.0783 | 0.1354 | 30 | 1.0955 |
0.716 | 0.2707 | 60 | 0.7190 |
0.6167 | 0.4061 | 90 | 0.6266 |
0.6226 | 0.5415 | 120 | 0.5929 |
0.5665 | 0.6768 | 150 | 0.5737 |
0.5834 | 0.8122 | 180 | 0.5621 |
0.5931 | 0.9475 | 210 | 0.5549 |
0.5431 | 1.0829 | 240 | 0.5496 |
0.5678 | 1.2183 | 270 | 0.5458 |
0.5336 | 1.3536 | 300 | 0.5425 |
0.5292 | 1.4890 | 330 | 0.5403 |
0.5627 | 1.6244 | 360 | 0.5384 |
0.5493 | 1.7597 | 390 | 0.5374 |
0.5154 | 1.8951 | 420 | 0.5367 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1