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.
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
Runs of athirdpath Harmonia-no_robots-20b on huggingface.co
13
Total runs
0
24-hour runs
-5
3-day runs
-4
7-day runs
-2
30-day runs
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