mistral-qlora_v1

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

• Loss: 1.2592
• Mean Token Accuracy: 0.6911
• Num Tokens: 896294

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Token Accuracy	Num Tokens
1.2597	1.0	31	1.2732	0.6890	896294
1.2271	2.0	62	1.2592	0.6911	896294

Framework versions

• PEFT 0.12.0
• Transformers 4.44.2
• Pytorch 2.8.0+cu126
• Datasets 2.20.0
• Tokenizers 0.19.1