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---
base_model: mistralai/Mistral-7B-Instruct-v0.3
datasets:
- generator
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: mistral_7b_cosine_lr
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_cosine_lr
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3803
## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.03
- lr_scheduler_warmup_steps: 15
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0242 | 0.0366 | 10 | 0.6227 |
| 0.5884 | 0.0732 | 20 | 0.5310 |
| 0.519 | 0.1098 | 30 | 0.4930 |
| 0.4818 | 0.1465 | 40 | 0.4653 |
| 0.4722 | 0.1831 | 50 | 0.4537 |
| 0.4513 | 0.2197 | 60 | 0.4440 |
| 0.4481 | 0.2563 | 70 | 0.4377 |
| 0.4455 | 0.2929 | 80 | 0.4321 |
| 0.4344 | 0.3295 | 90 | 0.4271 |
| 0.4345 | 0.3661 | 100 | 0.4233 |
| 0.4296 | 0.4027 | 110 | 0.4186 |
| 0.4255 | 0.4394 | 120 | 0.4166 |
| 0.4173 | 0.4760 | 130 | 0.4131 |
| 0.4195 | 0.5126 | 140 | 0.4098 |
| 0.4143 | 0.5492 | 150 | 0.4067 |
| 0.4103 | 0.5858 | 160 | 0.4043 |
| 0.4124 | 0.6224 | 170 | 0.4021 |
| 0.4069 | 0.6590 | 180 | 0.3988 |
| 0.4041 | 0.6957 | 190 | 0.3981 |
| 0.4044 | 0.7323 | 200 | 0.3951 |
| 0.3989 | 0.7689 | 210 | 0.3912 |
| 0.3947 | 0.8055 | 220 | 0.3895 |
| 0.3945 | 0.8421 | 230 | 0.3868 |
| 0.3876 | 0.8787 | 240 | 0.3849 |
| 0.3877 | 0.9153 | 250 | 0.3839 |
| 0.3922 | 0.9519 | 260 | 0.3817 |
| 0.3844 | 0.9886 | 270 | 0.3796 |
| 0.3491 | 1.0252 | 280 | 0.3832 |
| 0.3291 | 1.0618 | 290 | 0.3821 |
| 0.3267 | 1.0984 | 300 | 0.3803 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0 |