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---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: mistralai/Mistral-7B-Instruct-v0.2
datasets:
- generator
model-index:
- name: cls_alldata_mistral_v1
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. -->
# cls_alldata_mistral_v1
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4126
## 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: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5676 | 0.1091 | 20 | 0.5817 |
| 0.5158 | 0.2183 | 40 | 0.5408 |
| 0.5124 | 0.3274 | 60 | 0.5162 |
| 0.4791 | 0.4366 | 80 | 0.4999 |
| 0.4762 | 0.5457 | 100 | 0.4850 |
| 0.4724 | 0.6548 | 120 | 0.4737 |
| 0.4423 | 0.7640 | 140 | 0.4611 |
| 0.4453 | 0.8731 | 160 | 0.4508 |
| 0.4179 | 0.9823 | 180 | 0.4412 |
| 0.3243 | 1.0914 | 200 | 0.4479 |
| 0.3198 | 1.2005 | 220 | 0.4383 |
| 0.3012 | 1.3097 | 240 | 0.4335 |
| 0.3135 | 1.4188 | 260 | 0.4315 |
| 0.3081 | 1.5280 | 280 | 0.4247 |
| 0.3048 | 1.6371 | 300 | 0.4193 |
| 0.322 | 1.7462 | 320 | 0.4150 |
| 0.3034 | 1.8554 | 340 | 0.4136 |
| 0.3188 | 1.9645 | 360 | 0.4126 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |