metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
model-index:
- name: qlora-mistral-hackatone-yandexq
results: []
qlora-mistral-hackatone-yandexq
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8327
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 60
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.0167 | 1.0 | 1 | 1.9699 |
| 2.0949 | 2.0 | 2 | 1.9681 |
| 2.0703 | 3.0 | 3 | 1.9624 |
| 2.0674 | 4.0 | 4 | 1.9563 |
| 2.0057 | 5.0 | 5 | 1.9500 |
| 2.0534 | 6.0 | 6 | 1.9431 |
| 1.9912 | 7.0 | 7 | 1.9359 |
| 2.0333 | 8.0 | 8 | 1.9285 |
| 1.9934 | 9.0 | 9 | 1.9210 |
| 2.0358 | 10.0 | 10 | 1.9136 |
| 1.9727 | 11.0 | 11 | 1.9064 |
| 1.9698 | 12.0 | 12 | 1.8994 |
| 1.9983 | 13.0 | 13 | 1.8928 |
| 1.981 | 14.0 | 14 | 1.8865 |
| 1.9554 | 15.0 | 15 | 1.8807 |
| 1.935 | 16.0 | 16 | 1.8755 |
| 1.9203 | 17.0 | 17 | 1.8705 |
| 1.9371 | 18.0 | 18 | 1.8663 |
| 1.9184 | 19.0 | 19 | 1.8625 |
| 1.938 | 20.0 | 20 | 1.8592 |
| 1.94 | 21.0 | 21 | 1.8565 |
| 1.9062 | 22.0 | 22 | 1.8542 |
| 1.9293 | 23.0 | 23 | 1.8520 |
| 1.9464 | 24.0 | 24 | 1.8503 |
| 1.9271 | 25.0 | 25 | 1.8488 |
| 1.8998 | 26.0 | 26 | 1.8473 |
| 1.9393 | 27.0 | 27 | 1.8461 |
| 1.9188 | 28.0 | 28 | 1.8449 |
| 1.9117 | 29.0 | 29 | 1.8438 |
| 1.8974 | 30.0 | 30 | 1.8428 |
| 1.9181 | 31.0 | 31 | 1.8418 |
| 1.9047 | 32.0 | 32 | 1.8409 |
| 1.8977 | 33.0 | 33 | 1.8400 |
| 1.8937 | 34.0 | 34 | 1.8392 |
| 1.8801 | 35.0 | 35 | 1.8385 |
| 1.9149 | 36.0 | 36 | 1.8377 |
| 1.9027 | 37.0 | 37 | 1.8372 |
| 1.9076 | 38.0 | 38 | 1.8366 |
| 1.8718 | 39.0 | 39 | 1.8362 |
| 1.9125 | 40.0 | 40 | 1.8357 |
| 1.8903 | 41.0 | 41 | 1.8353 |
| 1.8668 | 42.0 | 42 | 1.8350 |
| 1.8653 | 43.0 | 43 | 1.8347 |
| 1.9068 | 44.0 | 44 | 1.8345 |
| 1.869 | 45.0 | 45 | 1.8342 |
| 1.8844 | 46.0 | 46 | 1.8340 |
| 1.9001 | 47.0 | 47 | 1.8338 |
| 1.886 | 48.0 | 48 | 1.8336 |
| 1.8847 | 49.0 | 49 | 1.8335 |
| 1.8566 | 50.0 | 50 | 1.8333 |
| 1.8729 | 51.0 | 51 | 1.8332 |
| 1.8736 | 52.0 | 52 | 1.8330 |
| 1.9098 | 53.0 | 53 | 1.8330 |
| 1.897 | 54.0 | 54 | 1.8329 |
| 1.8966 | 55.0 | 55 | 1.8328 |
| 1.8942 | 56.0 | 56 | 1.8328 |
| 1.871 | 57.0 | 57 | 1.8328 |
| 1.8434 | 58.0 | 58 | 1.8327 |
| 1.8743 | 59.0 | 59 | 1.8327 |
| 1.8472 | 60.0 | 60 | 1.8327 |
Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2