metadata
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
- dolly
- ipex
- max series gpu
base_model: microsoft/phi-1_5
datasets:
- generator
model-index:
- name: lora_phi-1_5
results: []
lora_phi-1_5
This model is a fine-tuned version of microsoft/phi-1_5 on the databricks/databricks-dolly-15k dataset. It achieves the following results on the evaluation set:
- Loss: 2.3998
Model description
This is a fine-tuned version of the microsoft/phi-1_5 model using Parameter Efficient Fine Tuning (PEFT) with Low Rank Adaptation (LoRA) on Intel(R) Data Center GPU Max 1100 and Intel(R) Xeon(R) Platinum 8480+ CPU . This model can be used for various text generation tasks including chatbots, content creation, and other NLP applications.
Training Hardware
This model was trained using: GPU:
- Intel(R) Data Center GPU Max 1100
- CPU: Intel(R) Xeon(R) Platinum 8480+
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 593
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.7756 | 0.8065 | 100 | 2.5791 |
| 2.558 | 1.6129 | 200 | 2.4656 |
| 2.4521 | 2.4194 | 300 | 2.4294 |
| 2.4589 | 3.2258 | 400 | 2.4103 |
| 2.4248 | 4.0323 | 500 | 2.3998 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.0.post0+cxx11.abi
- Datasets 2.19.1
- Tokenizers 0.19.1