metadata
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.3
model-index:
- name: finetuned_mistral_on_ads
results: []
finetuned_mistral_on_ads
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5249
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.7417 | 0.0444 | 2 | 3.6685 |
| 3.6314 | 0.0889 | 4 | 3.2304 |
| 3.0686 | 0.1333 | 6 | 2.8771 |
| 2.5057 | 0.1778 | 8 | 2.7170 |
| 2.5453 | 0.2222 | 10 | 2.5886 |
| 2.5759 | 0.2667 | 12 | 2.4625 |
| 2.4252 | 0.3111 | 14 | 2.3477 |
| 2.4227 | 0.3556 | 16 | 2.2455 |
| 1.987 | 0.4 | 18 | 2.1370 |
| 2.0229 | 0.4444 | 20 | 2.0484 |
| 2.0755 | 0.4889 | 22 | 1.9746 |
| 1.9004 | 0.5333 | 24 | 1.9032 |
| 1.9381 | 0.5778 | 26 | 1.8405 |
| 1.7879 | 0.6222 | 28 | 1.7911 |
| 1.7544 | 0.6667 | 30 | 1.7584 |
| 1.7485 | 0.7111 | 32 | 1.7290 |
| 1.6927 | 0.7556 | 34 | 1.7030 |
| 1.8931 | 0.8 | 36 | 1.6825 |
| 1.5624 | 0.8444 | 38 | 1.6656 |
| 1.7061 | 0.8889 | 40 | 1.6528 |
| 1.7288 | 0.9333 | 42 | 1.6426 |
| 1.7839 | 0.9778 | 44 | 1.6347 |
| 1.5954 | 1.0222 | 46 | 1.6270 |
| 1.4288 | 1.0667 | 48 | 1.6177 |
| 1.5201 | 1.1111 | 50 | 1.6094 |
| 1.5281 | 1.1556 | 52 | 1.6037 |
| 1.4132 | 1.2 | 54 | 1.5998 |
| 1.4271 | 1.2444 | 56 | 1.5976 |
| 1.4778 | 1.2889 | 58 | 1.5952 |
| 1.5138 | 1.3333 | 60 | 1.5921 |
| 1.4539 | 1.3778 | 62 | 1.5875 |
| 1.4293 | 1.4222 | 64 | 1.5823 |
| 1.3673 | 1.4667 | 66 | 1.5773 |
| 1.5272 | 1.5111 | 68 | 1.5734 |
| 1.506 | 1.5556 | 70 | 1.5701 |
| 1.2929 | 1.6 | 72 | 1.5669 |
| 1.387 | 1.6444 | 74 | 1.5637 |
| 1.3375 | 1.6889 | 76 | 1.5609 |
| 1.4666 | 1.7333 | 78 | 1.5586 |
| 1.2295 | 1.7778 | 80 | 1.5553 |
| 1.5195 | 1.8222 | 82 | 1.5521 |
| 1.5116 | 1.8667 | 84 | 1.5488 |
| 1.2947 | 1.9111 | 86 | 1.5449 |
| 1.4651 | 1.9556 | 88 | 1.5399 |
| 1.5171 | 2.0 | 90 | 1.5351 |
| 1.1823 | 2.0444 | 92 | 1.5312 |
| 1.3729 | 2.0889 | 94 | 1.5286 |
| 1.2607 | 2.1333 | 96 | 1.5256 |
| 1.2048 | 2.1778 | 98 | 1.5237 |
| 1.2862 | 2.2222 | 100 | 1.5229 |
| 1.2584 | 2.2667 | 102 | 1.5224 |
| 1.2285 | 2.3111 | 104 | 1.5223 |
| 1.2794 | 2.3556 | 106 | 1.5222 |
| 1.2196 | 2.4 | 108 | 1.5227 |
| 1.2526 | 2.4444 | 110 | 1.5232 |
| 1.2876 | 2.4889 | 112 | 1.5237 |
| 1.1812 | 2.5333 | 114 | 1.5247 |
| 1.3622 | 2.5778 | 116 | 1.5255 |
| 1.229 | 2.6222 | 118 | 1.5261 |
| 1.2796 | 2.6667 | 120 | 1.5262 |
| 1.2059 | 2.7111 | 122 | 1.5258 |
| 1.3327 | 2.7556 | 124 | 1.5257 |
| 1.254 | 2.8 | 126 | 1.5257 |
| 1.2183 | 2.8444 | 128 | 1.5256 |
| 1.1979 | 2.8889 | 130 | 1.5254 |
| 1.2558 | 2.9333 | 132 | 1.5251 |
| 1.1405 | 2.9778 | 134 | 1.5249 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1