File size: 3,062 Bytes
1f1a9f0 58bb8d6 1f1a9f0 58bb8d6 1f1a9f0 58bb8d6 1f1a9f0 58bb8d6 1f1a9f0 58bb8d6 1f1a9f0 |
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 75 76 77 78 79 80 81 82 83 84 |
---
base_model: microsoft/Phi-3.5-mini-instruct
library_name: peft
license: mit
metrics:
- rouge
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: grounded-ai-rag-3
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/josh-longenecker1-groundedai/grounded-ai-rag-relevance/runs/oius6vlo)
# grounded-ai-rag-3
This model is a fine-tuned version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3813
- Rouge1: 1.0
- Rouge2: 0.0
- Rougel: 1.0
- Rougelsum: 1.0
## 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: 7e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 15
- training_steps: 150
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 1.7953 | 5.0 | 5 | 1.8076 | 1.0 | 0.0 | 1.0 | 1.0 |
| 1.4603 | 10.0 | 10 | 1.6034 | 1.0 | 0.0 | 1.0 | 1.0 |
| 1.2107 | 15.0 | 15 | 1.4092 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.911 | 20.0 | 20 | 1.2036 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.5225 | 25.0 | 25 | 1.0263 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.2248 | 30.0 | 30 | 0.9228 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.1138 | 35.0 | 35 | 0.9692 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0533 | 40.0 | 40 | 1.1089 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0197 | 45.0 | 45 | 1.1951 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0066 | 50.0 | 50 | 1.2534 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0051 | 55.0 | 55 | 1.3186 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0036 | 60.0 | 60 | 1.3523 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0047 | 65.0 | 65 | 1.3669 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0037 | 70.0 | 70 | 1.3813 | 1.0 | 0.0 | 1.0 | 1.0 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1 |