---
base_model: mistralai/Mistral-7B-Instruct-v0.2
datasets:
- generator
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: ICSR_classification_finetuned_mistral_adapters_V100_test
  results: []
---

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# ICSR_classification_finetuned_mistral_adapters_V100_test

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: 1.0845

## 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: 4
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1907        | 0.1996 | 100  | 1.1196          |
| 1.1121        | 0.3992 | 200  | 1.1080          |
| 1.1002        | 0.5988 | 300  | 1.0956          |
| 1.0871        | 0.7984 | 400  | 1.0866          |
| 1.0808        | 0.9980 | 500  | 1.0845          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.44.0
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1