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This was mostly a test to see what the loss/eval looked like when training on top of Harmonia, and in that sense it was a sterling success, without the "jitter" I experienced training on top of Nethena 20b. Quick testing shows a bit of derpiness, but a nice conversational flow. Overall, this will be helpful in developing additional 20b merges.

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NOTES

This model is a fine-tuned version of athirdpath/Harmonia-20B on the HF No Robots dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4881

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: 3.5e-05
  • train_batch_size: 3
  • eval_batch_size: 3
  • seed: 42
  • gradient_accumulation_steps: 3
  • total_train_batch_size: 9
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 10
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
1.5598 0.55 50 1.5816
1.5384 1.08 100 1.5146
1.5362 1.64 150 1.4972
1.4234 2.17 200 1.4902
1.4678 2.72 250 1.4881

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Finetuned from

Collection including athirdpath/Harmonia-no_robots-20b