README.md

metadata

library_name: peft
license: other
base_model: mistralai/Mistral-7B-Instruct-v0.3
tags:
  - llama-factory
  - lora
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: factory_mistral_results
    results: []

factory_mistral_results

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on the train dataset. It achieves the following results on the evaluation set:

• Loss: 0.2260
• Accuracy: 0.9587

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: 0.0001
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• total_eval_batch_size: 8
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.03
• num_epochs: 9.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3179	1.0	32	0.3321	0.9217
0.206	2.0	64	0.2425	0.9408
0.1447	3.0	96	0.2109	0.9489
0.1067	4.0	128	0.2062	0.9527
0.0612	5.0	160	0.2128	0.9539
0.0491	6.0	192	0.2169	0.9549
0.0378	7.0	224	0.2166	0.9584
0.0294	8.0	256	0.2224	0.9588
0.0215	9.0	288	0.2260	0.9587

Framework versions

• PEFT 0.15.2
• Transformers 4.52.4
• Pytorch 2.7.0
• Datasets 3.6.0
• Tokenizers 0.21.1