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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
datasets:
- mbe
metrics:
- accuracy
model-index:
- name: Mistral-7B-v0.1_mbe_no
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-v0.1_mbe_no
This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the mbe dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5616
- Accuracy: 0.5362
## 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
- gradient_accumulation_steps: 4
- total_train_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
- training_steps: 300
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5245 | 0.07 | 10 | 0.6507 | 0.3355 |
| 0.6666 | 0.13 | 20 | 0.6464 | 0.3816 |
| 0.6527 | 0.2 | 30 | 0.6427 | 0.3684 |
| 0.6168 | 0.27 | 40 | 0.6321 | 0.3980 |
| 0.6584 | 0.33 | 50 | 0.6182 | 0.3914 |
| 0.586 | 0.4 | 60 | 0.6244 | 0.4145 |
| 0.5924 | 0.47 | 70 | 0.6034 | 0.4342 |
| 0.6069 | 0.53 | 80 | 0.6096 | 0.4375 |
| 0.5999 | 0.6 | 90 | 0.6096 | 0.4408 |
| 0.6206 | 0.67 | 100 | 0.6070 | 0.4572 |
| 0.5793 | 0.73 | 110 | 0.6016 | 0.4572 |
| 0.6208 | 0.8 | 120 | 0.5902 | 0.4605 |
| 0.5622 | 0.87 | 130 | 0.5775 | 0.4770 |
| 0.5502 | 0.93 | 140 | 0.5761 | 0.4671 |
| 0.5958 | 1.0 | 150 | 0.5606 | 0.4901 |
| 0.4558 | 1.07 | 160 | 0.5840 | 0.4737 |
| 0.4411 | 1.14 | 170 | 0.5631 | 0.4901 |
| 0.4144 | 1.2 | 180 | 0.5745 | 0.5 |
| 0.4647 | 1.27 | 190 | 0.5932 | 0.4605 |
| 0.4504 | 1.34 | 200 | 0.5799 | 0.5099 |
| 0.4299 | 1.4 | 210 | 0.6488 | 0.4934 |
| 0.425 | 1.47 | 220 | 0.5704 | 0.5132 |
| 0.4152 | 1.54 | 230 | 0.5582 | 0.5066 |
| 0.425 | 1.6 | 240 | 0.5489 | 0.5329 |
| 0.446 | 1.67 | 250 | 0.5479 | 0.5197 |
| 0.3908 | 1.74 | 260 | 0.5564 | 0.5164 |
| 0.443 | 1.8 | 270 | 0.5419 | 0.5033 |
| 0.4081 | 1.87 | 280 | 0.5948 | 0.5066 |
| 0.3944 | 1.94 | 290 | 0.5547 | 0.5395 |
| 0.4005 | 2.0 | 300 | 0.5616 | 0.5362 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.1
- Tokenizers 0.15.1 |