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---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- unsloth
- unsloth
- unsloth
- generated_from_trainer
base_model: unsloth/mistral-7b-instruct-v0.2-bnb-4bit
model-index:
- name: mistral-7b-instruct-v0.2-bnb-4bit1024
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. -->
# mistral-7b-instruct-v0.2-bnb-4bit1024
This model is a fine-tuned version of [unsloth/mistral-7b-instruct-v0.2-bnb-4bit](https://huggingface.co/unsloth/mistral-7b-instruct-v0.2-bnb-4bit) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6953
## 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: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8431 | 0.02 | 25 | 1.4131 |
| 0.8021 | 0.04 | 50 | 0.7911 |
| 0.7972 | 0.05 | 75 | 0.7886 |
| 0.7886 | 0.07 | 100 | 0.7780 |
| 0.7762 | 0.09 | 125 | 0.7546 |
| 0.7338 | 0.11 | 150 | 0.7332 |
| 0.707 | 0.12 | 175 | 0.7399 |
| 0.7252 | 0.14 | 200 | 0.7303 |
| 0.7513 | 0.16 | 225 | 0.7384 |
| 0.7275 | 0.18 | 250 | 0.7380 |
| 0.7283 | 0.19 | 275 | 0.7285 |
| 0.7132 | 0.21 | 300 | 0.7452 |
| 0.7273 | 0.23 | 325 | 0.7370 |
| 0.7353 | 0.25 | 350 | 0.7388 |
| 0.7457 | 0.27 | 375 | 0.7292 |
| 0.7404 | 0.28 | 400 | 0.7315 |
| 0.7312 | 0.3 | 425 | 0.7341 |
| 0.7285 | 0.32 | 450 | 0.7277 |
| 0.7331 | 0.34 | 475 | 0.7318 |
| 0.7179 | 0.35 | 500 | 0.7401 |
| 0.7432 | 0.37 | 525 | 0.7399 |
| 0.7305 | 0.39 | 550 | 0.7463 |
| 0.723 | 0.41 | 575 | 0.7448 |
| 0.7303 | 0.42 | 600 | 0.7339 |
| 0.7213 | 0.44 | 625 | 0.7320 |
| 0.7236 | 0.46 | 650 | 0.7378 |
| 0.7263 | 0.48 | 675 | 0.7451 |
| 0.7462 | 0.5 | 700 | 0.7238 |
| 0.7287 | 0.51 | 725 | 0.7274 |
| 0.7364 | 0.53 | 750 | 0.7369 |
| 0.7276 | 0.55 | 775 | 0.7282 |
| 0.7268 | 0.57 | 800 | 0.7431 |
| 0.7382 | 0.58 | 825 | 0.7376 |
| 0.7185 | 0.6 | 850 | 0.7402 |
| 0.7153 | 0.62 | 875 | 0.7362 |
| 0.7314 | 0.64 | 900 | 0.7395 |
| 0.7465 | 0.65 | 925 | 0.7378 |
| 0.7228 | 0.67 | 950 | 0.7333 |
| 0.7336 | 0.69 | 975 | 0.7337 |
| 0.72 | 0.71 | 1000 | 0.7313 |
| 0.7258 | 0.73 | 1025 | 0.7379 |
| 0.7312 | 0.74 | 1050 | 0.7342 |
| 0.7268 | 0.76 | 1075 | 0.7350 |
| 0.7137 | 0.78 | 1100 | 0.7401 |
| 0.7277 | 0.8 | 1125 | 0.7277 |
| 0.7314 | 0.81 | 1150 | 0.7388 |
| 0.7106 | 0.83 | 1175 | 0.7371 |
| 0.7226 | 0.85 | 1200 | 0.7326 |
| 0.7262 | 0.87 | 1225 | 0.7328 |
| 0.7356 | 0.88 | 1250 | 0.7408 |
| 0.7245 | 0.9 | 1275 | 0.7365 |
| 0.7221 | 0.92 | 1300 | 0.7404 |
| 0.7194 | 0.94 | 1325 | 0.7418 |
| 0.7209 | 0.96 | 1350 | 0.7380 |
| 0.7205 | 0.97 | 1375 | 0.7279 |
| 0.6788 | 0.99 | 1400 | 0.6953 |
### Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1 |