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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
model-index:
- name: Mistral-7B-Instruct-v0.2-binary_base02
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-binary_base02
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2468
## 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: 2.5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3861 | 0.32 | 50 | 0.5395 |
| 0.4528 | 0.63 | 100 | 0.3798 |
| 0.3429 | 0.95 | 150 | 0.3177 |
| 0.2952 | 1.27 | 200 | 0.3050 |
| 0.2816 | 1.59 | 250 | 0.2726 |
| 0.2661 | 1.9 | 300 | 0.2615 |
| 0.2498 | 2.22 | 350 | 0.2545 |
| 0.2439 | 2.54 | 400 | 0.2565 |
| 0.2471 | 2.86 | 450 | 0.2504 |
| 0.2417 | 3.17 | 500 | 0.2522 |
| 0.2372 | 3.49 | 550 | 0.2481 |
| 0.2312 | 3.81 | 600 | 0.2429 |
| 0.2266 | 4.13 | 650 | 0.2481 |
| 0.2179 | 4.44 | 700 | 0.2459 |
| 0.2221 | 4.76 | 750 | 0.2409 |
| 0.2165 | 5.08 | 800 | 0.2470 |
| 0.2064 | 5.4 | 850 | 0.2464 |
| 0.2062 | 5.71 | 900 | 0.2448 |
| 0.2087 | 6.03 | 950 | 0.2449 |
| 0.1975 | 6.35 | 1000 | 0.2468 |
### Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0 |