File size: 2,157 Bytes
3776207 6ba32ea 3776207 38a2e5a 3776207 ab7bb42 38a2e5a 3776207 d30bc0c caca030 3776207 e8b9315 6ba32ea 60d4ada 6ba32ea 3776207 38a2e5a 60d4ada 3776207 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 |
---
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: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# lora_phi-1_5
This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the [databricks/databricks-dolly-15k](https://huggingface.co/datasets/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](https://huggingface.co/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 |