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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_2e-4_bs2
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_2e-4_bs2
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: 0.3819
## 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
- lr_scheduler_warmup_ratio: 0.03
- lr_scheduler_warmup_steps: 15
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 3.5854 | 0.0366 | 10 | 0.7044 |
| 0.6542 | 0.0732 | 20 | 0.8683 |
| 0.5736 | 0.1098 | 30 | 0.5023 |
| 0.4886 | 0.1465 | 40 | 0.4735 |
| 0.4757 | 0.1831 | 50 | 0.4552 |
| 0.453 | 0.2197 | 60 | 0.4451 |
| 0.4494 | 0.2563 | 70 | 0.4380 |
| 0.4457 | 0.2929 | 80 | 0.4329 |
| 0.4353 | 0.3295 | 90 | 0.4271 |
| 0.434 | 0.3661 | 100 | 0.4239 |
| 0.4307 | 0.4027 | 110 | 0.4198 |
| 0.4256 | 0.4394 | 120 | 0.4167 |
| 0.4173 | 0.4760 | 130 | 0.4130 |
| 0.4195 | 0.5126 | 140 | 0.4100 |
| 0.4159 | 0.5492 | 150 | 0.4075 |
| 0.4102 | 0.5858 | 160 | 0.4045 |
| 0.4135 | 0.6224 | 170 | 0.4034 |
| 0.408 | 0.6590 | 180 | 0.4004 |
| 0.405 | 0.6957 | 190 | 0.3992 |
| 0.4053 | 0.7323 | 200 | 0.3960 |
| 0.3994 | 0.7689 | 210 | 0.3934 |
| 0.3968 | 0.8055 | 220 | 0.3914 |
| 0.3966 | 0.8421 | 230 | 0.3885 |
| 0.3894 | 0.8787 | 240 | 0.3868 |
| 0.3896 | 0.9153 | 250 | 0.3860 |
| 0.3939 | 0.9519 | 260 | 0.3836 |
| 0.387 | 0.9886 | 270 | 0.3818 |
| 0.3511 | 1.0252 | 280 | 0.3839 |
| 0.3316 | 1.0618 | 290 | 0.3834 |
| 0.3281 | 1.0984 | 300 | 0.3819 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0 |