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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: 5.3993
## 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: 0.003
- train_batch_size: 3
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 24
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 11.1885 | 0.0549 | 10 | 61.4970 |
| 37.6512 | 0.1098 | 20 | 12.9405 |
| 14.576 | 0.1647 | 30 | 27.9852 |
| 9.5892 | 0.2196 | 40 | 6.4722 |
| 7.7639 | 0.2745 | 50 | 6.8158 |
| 6.3878 | 0.3294 | 60 | 6.3811 |
| 6.6118 | 0.3844 | 70 | 5.9281 |
| 6.006 | 0.4393 | 80 | 5.6753 |
| 6.1011 | 0.4942 | 90 | 5.8083 |
| 5.7396 | 0.5491 | 100 | 5.6193 |
| 5.5128 | 0.6040 | 110 | 5.4848 |
| 5.4599 | 0.6589 | 120 | 5.4267 |
| 5.5193 | 0.7138 | 130 | 5.4757 |
| 5.4488 | 0.7687 | 140 | 5.4422 |
| 5.4257 | 0.8236 | 150 | 5.3845 |
| 5.3938 | 0.8785 | 160 | 5.3727 |
| 5.3937 | 0.9334 | 170 | 5.3646 |
| 5.3916 | 0.9883 | 180 | 5.4825 |
| 5.4217 | 1.0432 | 190 | 5.3534 |
| 5.3915 | 1.0981 | 200 | 5.3497 |
| 5.3656 | 1.1531 | 210 | 5.3416 |
| 5.3718 | 1.2080 | 220 | 5.3691 |
| 5.3763 | 1.2629 | 230 | 5.4102 |
| 5.4039 | 1.3178 | 240 | 5.3993 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0 |