metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: Mistral-7B-v0.1_caselaw
results: []
Mistral-7B-v0.1_caselaw
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1640
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.2324 | 0.07 | 50 | 1.2373 |
| 1.2114 | 0.13 | 100 | 1.2199 |
| 1.1831 | 0.2 | 150 | 1.2111 |
| 1.2027 | 0.26 | 200 | 1.2048 |
| 1.1827 | 0.33 | 250 | 1.2001 |
| 1.1696 | 0.39 | 300 | 1.1973 |
| 1.2186 | 0.46 | 350 | 1.1938 |
| 1.1795 | 0.52 | 400 | 1.1919 |
| 1.2167 | 0.59 | 450 | 1.1884 |
| 1.1992 | 0.66 | 500 | 1.1840 |
| 1.2032 | 0.72 | 550 | 1.1824 |
| 1.1841 | 0.79 | 600 | 1.1798 |
| 1.166 | 0.85 | 650 | 1.1789 |
| 1.1641 | 0.92 | 700 | 1.1761 |
| 1.1859 | 0.98 | 750 | 1.1752 |
| 1.132 | 1.05 | 800 | 1.1736 |
| 1.1461 | 1.12 | 850 | 1.1724 |
| 1.0965 | 1.18 | 900 | 1.1726 |
| 1.1064 | 1.25 | 950 | 1.1724 |
| 1.123 | 1.31 | 1000 | 1.1729 |
| 1.1079 | 1.38 | 1050 | 1.1695 |
| 1.12 | 1.44 | 1100 | 1.1707 |
| 1.1288 | 1.51 | 1150 | 1.1693 |
| 1.133 | 1.57 | 1200 | 1.1676 |
| 1.1647 | 1.64 | 1250 | 1.1693 |
| 1.1269 | 1.71 | 1300 | 1.1658 |
| 1.1332 | 1.77 | 1350 | 1.1657 |
| 1.1276 | 1.84 | 1400 | 1.1681 |
| 1.1361 | 1.9 | 1450 | 1.1633 |
| 1.1205 | 1.97 | 1500 | 1.1640 |
Framework versions
- PEFT 0.7.1
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.1
- Tokenizers 0.15.1