File size: 2,807 Bytes
7a1a66b |
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 85 86 87 88 89 |
---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
model-index:
- name: Mistral-7B-Instruct-v0.2-mirage-all-teacher-instruct-mistral-sft
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. -->
# Mistral-7B-Instruct-v0.2-mirage-all-teacher-instruct-mistral-sft
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9628
## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.3478 | 0.0412 | 200 | 1.2310 |
| 1.3495 | 0.0824 | 400 | 1.1826 |
| 1.3753 | 0.1237 | 600 | 1.1557 |
| 1.3454 | 0.1649 | 800 | 1.1297 |
| 1.2731 | 0.2061 | 1000 | 1.1071 |
| 1.3863 | 0.2473 | 1200 | 1.0878 |
| 1.2567 | 0.2885 | 1400 | 1.0777 |
| 1.257 | 0.3298 | 1600 | 1.0630 |
| 1.2129 | 0.3710 | 1800 | 1.0518 |
| 1.1939 | 0.4122 | 2000 | 1.0405 |
| 1.2658 | 0.4534 | 2200 | 1.0313 |
| 1.1718 | 0.4946 | 2400 | 1.0186 |
| 1.1795 | 0.5359 | 2600 | 1.0102 |
| 1.1984 | 0.5771 | 2800 | 1.0008 |
| 1.157 | 0.6183 | 3000 | 0.9930 |
| 1.1542 | 0.6595 | 3200 | 0.9862 |
| 1.1648 | 0.7007 | 3400 | 0.9802 |
| 1.1403 | 0.7420 | 3600 | 0.9750 |
| 1.1268 | 0.7832 | 3800 | 0.9705 |
| 1.2122 | 0.8244 | 4000 | 0.9672 |
| 1.0571 | 0.8656 | 4200 | 0.9649 |
| 1.0903 | 0.9068 | 4400 | 0.9635 |
| 1.178 | 0.9481 | 4600 | 0.9629 |
| 1.1661 | 0.9893 | 4800 | 0.9628 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |