Frostwind-10.7B-v1-exl2

8bpw 8h

Frostwind-v1

A finetune of upstage/SOLAR-10.7B-v1.0 <br>Took Roughly 3 Hours with 4x 4090s, over 2 Epochs, with around 52K varied samples.

Dataset Composition: <br>20% - Coding <br>30% - Instruct <br>30% - Generalised Data <br>10% - Roleplay <br>10% - Dealignment

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Testing Notes:

Fairly smart, as I expected. Obviously not at the level of the bigger models, but I did not expect that level from this.

Could be sampler issues, but generally I needed 1/2 swipes to get the correct answer when doing Zero context tests. If context is filled, no issues on my end.

For Roleplays: adding things like avoid writing as {{user}} suprisingly helps. Plus a proper prompt of course. I liked the writing style. Handles group characters in 1 card well, during my tests.

Fairly uncensored during roleplay. Yeah the as an AI stuff can happen at Zero context, but I have no issues once a character card is introduced. I had no issues making outputs that would give me 2500 Life Sentences if posted here.

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Trained with Alpaca Format:

### Instruction:
<Prompt>

### Response:

OR

### Instruction:
<Prompt>

### Input:
<Insert Context Here>

### Response:

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<br>wandb: <br>wandb: Run history: <br>wandb: eval/loss █▃▂▂▂▂▂▁▁▁▁▂▂▂▂▂▂▁▁▁ <br>wandb: eval/runtime ▃▂▃▂▃▂▂▃▁▃█▂▃▃▃▂▃▃▂▂ <br>wandb: eval/samples_per_second ▆▇▆▇▆▇▇▆█▆▁▇▆▆▆▇▆▆▇▇ <br>wandb: eval/steps_per_second ▆▇▆▇▆▇▇▆█▆▁▇▆▆▆▇▆▆▇▇ <br>wandb: train/epoch ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ <br>wandb: train/global_step ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ <br>wandb: train/learning_rate ▄███████▇▇▇▇▇▆▆▆▆▅▅▅▅▄▄▄▃▃▃▃▂▂▂▂▂▁▁▁▁▁▁▁ <br>wandb: train/loss █▅▅▆▅▅▄▄▄▆▆▅▆▆▆▅▄▆▅▅▅▆▄▄▃▄▃▃▂▃▄▂▂▃▃▂▁▂▂▂ <br>wandb: <br>wandb: Run summary: <br>wandb: eval/loss 0.74622 <br>wandb: eval/runtime 72.5049 <br>wandb: eval/samples_per_second 37.239 <br>wandb: eval/steps_per_second 2.331 <br>wandb: train/epoch 1.98 <br>wandb: train/global_step 410 <br>wandb: train/learning_rate 0.0 <br>wandb: train/loss 0.6457 <br>wandb: train/total_flos 3.4382652340646707e+18 <br>wandb: train/train_loss 0.70204 <br>wandb: train/train_runtime 10880.917 <br>wandb: train/train_samples_per_second 9.417 <br>wandb: train/train_steps_per_second 0.038 <br>wandb: