metadata
license: mit
base_model: microsoft/phi-1_5
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
model-index:
- name: phi-1_5_sft
results: []
phi-1_5_sft
This model is a fine-tuned version of microsoft/phi-1_5 on the HuggingFaceH4/ultrachat_200k dataset. It achieves the following results on the evaluation set:
- Loss: 1.2542
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 120
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3099 | 0.1 | 100 | 1.3398 |
| 1.3131 | 0.2 | 200 | 1.3159 |
| 1.3009 | 0.3 | 300 | 1.3046 |
| 1.2915 | 0.4 | 400 | 1.2967 |
| 1.2714 | 0.5 | 500 | 1.2906 |
| 1.2811 | 0.6 | 600 | 1.2854 |
| 1.2621 | 0.7 | 700 | 1.2807 |
| 1.2406 | 0.8 | 800 | 1.2767 |
| 1.2371 | 0.9 | 900 | 1.2731 |
| 1.2547 | 1.0 | 1000 | 1.2699 |
| 1.2085 | 1.1 | 1100 | 1.2693 |
| 1.2253 | 1.2 | 1200 | 1.2669 |
| 1.215 | 1.3 | 1300 | 1.2649 |
| 1.2103 | 1.4 | 1400 | 1.2630 |
| 1.2081 | 1.5 | 1500 | 1.2612 |
| 1.2033 | 1.6 | 1600 | 1.2597 |
| 1.2307 | 1.7 | 1700 | 1.2582 |
| 1.2038 | 1.8 | 1800 | 1.2568 |
| 1.2014 | 1.9 | 1900 | 1.2557 |
| 1.188 | 2.0 | 2000 | 1.2546 |
| 1.1473 | 2.1 | 2100 | 1.2563 |
| 1.1872 | 2.2 | 2200 | 1.2559 |
| 1.2086 | 2.3 | 2300 | 1.2553 |
| 1.1896 | 2.4 | 2400 | 1.2550 |
| 1.1733 | 2.5 | 2500 | 1.2548 |
| 1.1665 | 2.6 | 2600 | 1.2544 |
| 1.1499 | 2.7 | 2700 | 1.2543 |
| 1.1779 | 2.8 | 2800 | 1.2542 |
| 1.1746 | 2.9 | 2900 | 1.2542 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0