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opt-125m-pattern-based_finetuning_with_lora-mnli-mm-d3_fs2 – AI Model by jeanlucmarsh | AlphaNeural AI
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jeanlucmarsh
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opt-125m-pattern-based_finetuning_with_lora-mnli-mm-d3_fs2
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peft
tensorboard
safetensors
generated_from_trainer
glue
facebook/opt-125m
adapter
other
us
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opt-125m-pattern-based_finetuning_with_lora-mnli-mm-d3_fs2
This model is a fine-tuned version of
facebook/opt-125m
on the glue dataset. It achieves the following results on the evaluation set:
Loss: 0.8122
Accuracy: 0.5104
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: 2e-06
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.6446
1.0
1
0.8122
0.5104
0.6665
2.0
2
0.8126
0.5104
0.6007
3.0
3
0.8130
0.5099
0.6147
4.0
4
0.8132
0.5101
0.6054
5.0
5
0.8133
0.5101
Framework versions
PEFT 0.7.1.dev0
Transformers 4.36.0.dev0
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0
