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
