Mistral-7B-Instruct-v0.1-LC-PI-.5-noSW

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Mistral-7B-Instruct-v0.1-LC-PI-.5-noSW

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.1 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.8995

Model description

This model is a fine-tuning of Mistral-7B-Instruct-v0.1. This FT was done with full attention (removing the 4k SWA). This FT was using a Position Interpolation factor of 0.5 (Linear RoPE scaling). Please note that the RoPE scaling factor should be determined by L/L' where L is the pre-training max context length and L' is the new max context length. In our case, we are just making experiments (and for us we would have had L/L' = 8096/7200 > 1 which did not require any PI scaling).

Intended uses & limitations

More information needed

Training and evaluation data

Data is a 9k sample from the RedPajama datset. The context is <=7200 with a decreasing exponential distribution of scale 1500.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 32
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 20
• training_steps: 300

Training results

Framework versions

• Transformers 4.34.1
• Pytorch 2.0.0+cu117
• Datasets 2.14.6
• Tokenizers 0.14.1