Use this text2text model to find out what LLM instructions might be able to generate an arbitary piece of code!
This model is a fine-tuned version of
facebook/bart-base
on the
pszemraj/fleece2instructions-codealpaca
dataset.
It achieves the following results on the evaluation set:
Loss: 1.0136
Rouge1: 59.9513
Rouge2: 33.9118
Rougel: 55.7815
Rougelsum: 56.9064
Gen Len: 29.7146
Intended uses & limitations
🚨
note:
as the authors elected to release the
original dataset
under
cc-by-nc
, the license carries over to this model and
cannot be used for commercial activity
.
This is just a
base
size model, which does a decent job for its size, but is not perfect. For better quality instructions, check out
bart-large
or fine tune your own larger model on the dataset :)
Intended use: Research on domain adaptation and/or other improvements to LLMs by extending instruction:text data pairs.
Training and evaluation data
Refer to the linked dataset card for
pszemraj/fleece2instructions-codealpaca
or the
original dataset
repo.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 8e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
gradient_accumulation_steps: 16
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.02
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
Gen Len
1.1165
1.0
281
1.1090
57.9239
31.9259
53.8737
54.9811
28.2924
1.0763
2.0
563
1.0267
59.9605
34.0298
55.7523
56.8021
29.6966
0.9595
2.99
843
1.0136
59.9513
33.9118
55.7815
56.9064
29.7146
Runs of pszemraj bart-base-code-instructiongen on huggingface.co
18
Total runs
0
24-hour runs
2
3-day runs
4
7-day runs
6
30-day runs
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