| | --- |
| | license: apache-2.0 |
| | library_name: peft |
| | tags: |
| | - trl |
| | - sft |
| | - generated_from_trainer |
| | base_model: mistralai/Mistral-7B-v0.1 |
| | datasets: |
| | - generator |
| | model-index: |
| | - name: lc_full_packing |
| | 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. --> |
| |
|
| | # lc_full_packing |
| |
|
| | This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the generator dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.6843 |
| |
|
| | ## 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: 2e-05 |
| | - train_batch_size: 1 |
| | - eval_batch_size: 1 |
| | - seed: 42 |
| | - 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 | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 1.658 | 1.0 | 80 | 1.6224 | |
| | | 1.5504 | 2.0 | 160 | 1.5658 | |
| | | 1.5401 | 3.0 | 240 | 1.5452 | |
| | | 1.5012 | 4.0 | 320 | 1.5356 | |
| | | 1.5873 | 5.0 | 400 | 1.5318 | |
| | | 1.4235 | 6.0 | 480 | 1.5295 | |
| | | 1.4938 | 7.0 | 560 | 1.5312 | |
| | | 1.4809 | 8.0 | 640 | 1.5340 | |
| | | 1.3717 | 9.0 | 720 | 1.5361 | |
| | | 1.5824 | 10.0 | 800 | 1.5430 | |
| | | 1.4478 | 11.0 | 880 | 1.5456 | |
| | | 1.4124 | 12.0 | 960 | 1.5535 | |
| | | 1.3804 | 13.0 | 1040 | 1.5635 | |
| | | 1.3416 | 14.0 | 1120 | 1.5694 | |
| | | 1.3678 | 15.0 | 1200 | 1.5820 | |
| | | 1.3439 | 16.0 | 1280 | 1.5922 | |
| | | 1.2532 | 17.0 | 1360 | 1.6031 | |
| | | 1.2628 | 18.0 | 1440 | 1.5963 | |
| | | 1.4167 | 19.0 | 1520 | 1.6095 | |
| | | 1.2727 | 20.0 | 1600 | 1.6200 | |
| | | 1.3244 | 21.0 | 1680 | 1.6197 | |
| | | 1.2597 | 22.0 | 1760 | 1.6325 | |
| | | 1.2578 | 23.0 | 1840 | 1.6415 | |
| | | 1.3411 | 24.0 | 1920 | 1.6453 | |
| | | 1.2795 | 25.0 | 2000 | 1.6495 | |
| | | 1.2928 | 26.0 | 2080 | 1.6509 | |
| | | 1.2235 | 27.0 | 2160 | 1.6586 | |
| | | 1.2335 | 28.0 | 2240 | 1.6604 | |
| | | 1.1769 | 29.0 | 2320 | 1.6701 | |
| | | 1.2284 | 30.0 | 2400 | 1.6681 | |
| | | 1.2416 | 31.0 | 2480 | 1.6704 | |
| | | 1.3158 | 32.0 | 2560 | 1.6737 | |
| | | 1.2734 | 33.0 | 2640 | 1.6806 | |
| | | 1.2803 | 34.0 | 2720 | 1.6815 | |
| | | 1.1976 | 35.0 | 2800 | 1.6803 | |
| | | 1.2457 | 36.0 | 2880 | 1.6801 | |
| | | 1.2039 | 37.0 | 2960 | 1.6831 | |
| | | 1.1931 | 38.0 | 3040 | 1.6824 | |
| | | 1.2337 | 39.0 | 3120 | 1.6841 | |
| | | 1.2167 | 40.0 | 3200 | 1.6833 | |
| | | 1.1514 | 41.0 | 3280 | 1.6847 | |
| | | 1.2817 | 42.0 | 3360 | 1.6841 | |
| | | 1.1658 | 43.0 | 3440 | 1.6837 | |
| | | 1.2635 | 44.0 | 3520 | 1.6841 | |
| | | 1.0984 | 45.0 | 3600 | 1.6842 | |
| | | 1.2229 | 46.0 | 3680 | 1.6843 | |
| | | 1.26 | 47.0 | 3760 | 1.6840 | |
| | | 1.1621 | 48.0 | 3840 | 1.6844 | |
| | | 1.2998 | 49.0 | 3920 | 1.6848 | |
| | | 1.2054 | 50.0 | 4000 | 1.6843 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.11.1 |
| | - Transformers 4.41.2 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.19.2 |
| | - Tokenizers 0.19.1 |
