metadata
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.1
tags:
- generated_from_trainer
model-index:
- name: mistral-instruct-adv-robust-50-sft-lora
results: []
mistral-instruct-adv-robust-50-sft-lora
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8817
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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.1318 | 0.12 | 1 | 2.8355 |
| 3.1318 | 1.12 | 2 | 2.6364 |
| 3.1318 | 2.12 | 3 | 2.4945 |
| 3.1318 | 3.12 | 4 | 2.5339 |
| 2.7386 | 4.12 | 5 | 2.3352 |
| 2.7386 | 5.12 | 6 | 2.2137 |
| 2.7386 | 6.12 | 7 | 2.1641 |
| 2.7386 | 7.12 | 8 | 2.1051 |
| 2.7386 | 8.12 | 9 | 2.0842 |
| 2.269 | 9.12 | 10 | 2.0479 |
| 2.269 | 10.12 | 11 | 1.9554 |
| 2.269 | 11.12 | 12 | 1.8555 |
| 2.269 | 12.12 | 13 | 1.7736 |
| 2.269 | 13.12 | 14 | 1.7906 |
| 1.9451 | 14.12 | 15 | 1.7737 |
| 1.9451 | 15.12 | 16 | 1.6677 |
| 1.9451 | 16.12 | 17 | 1.6411 |
| 1.9451 | 17.12 | 18 | 1.5739 |
| 1.9451 | 18.12 | 19 | 1.5334 |
| 1.6568 | 19.12 | 20 | 1.4794 |
| 1.6568 | 20.12 | 21 | 1.4008 |
| 1.6568 | 21.12 | 22 | 1.3625 |
| 1.6568 | 22.12 | 23 | 1.2964 |
| 1.6568 | 23.12 | 24 | 1.2041 |
| 1.3674 | 24.12 | 25 | 1.1971 |
| 1.3674 | 25.12 | 26 | 1.1571 |
| 1.3674 | 26.12 | 27 | 1.1080 |
| 1.3674 | 27.12 | 28 | 1.1099 |
| 1.3674 | 28.12 | 29 | 1.0930 |
| 1.145 | 29.12 | 30 | 1.0333 |
| 1.145 | 30.12 | 31 | 1.0096 |
| 1.145 | 31.12 | 32 | 1.0012 |
| 1.145 | 32.12 | 33 | 0.9266 |
| 1.145 | 33.12 | 34 | 0.9624 |
| 0.9987 | 34.12 | 35 | 0.9425 |
| 0.9987 | 35.12 | 36 | 0.9354 |
| 0.9987 | 36.12 | 37 | 0.9091 |
| 0.9987 | 37.12 | 38 | 0.9007 |
| 0.9987 | 38.12 | 39 | 0.9649 |
| 0.9071 | 39.12 | 40 | 0.9199 |
| 0.9071 | 40.12 | 41 | 0.8651 |
| 0.9071 | 41.12 | 42 | 0.8727 |
| 0.9071 | 42.12 | 43 | 0.8559 |
| 0.9071 | 43.12 | 44 | 0.8499 |
| 0.8522 | 44.12 | 45 | 0.8547 |
| 0.8522 | 45.12 | 46 | 0.8880 |
| 0.8522 | 46.12 | 47 | 0.8678 |
| 0.8522 | 47.12 | 48 | 0.8565 |
| 0.8522 | 48.12 | 49 | 0.8197 |
| 0.8153 | 49.12 | 50 | 0.8439 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0a0+32f93b1
- Datasets 2.14.6
- Tokenizers 0.14.1