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-tool-embedding
results: []
Phi-3.5-MultiCap-tool-embedding
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: 0.5080
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 |
|---|---|---|---|
| 0.6813 | 0.2256 | 50 | 0.6682 |
| 0.5534 | 0.4512 | 100 | 0.5627 |
| 0.5291 | 0.6768 | 150 | 0.5372 |
| 0.575 | 0.9024 | 200 | 0.5245 |
| 0.5066 | 1.1280 | 250 | 0.5170 |
| 0.4949 | 1.3536 | 300 | 0.5124 |
| 0.4666 | 1.5792 | 350 | 0.5095 |
| 0.5142 | 1.8049 | 400 | 0.5080 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1