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llama-160m-qqp – AI Model by Cheng98 | AlphaNeural AI
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Cheng98
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llama-160m-qqp
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transformers
pytorch
llama
text-classification
generated_from_trainer
JackFram/llama-160m
finetune
apache-2.0
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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llama-160m-qqp
This model is a fine-tuned version of
JackFram/llama-160m
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.5816
Accuracy: 0.6842
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: 5e-05
train_batch_size: 16
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.6019
1.0
2842
0.5971
0.6734
0.5849
2.0
5685
0.5836
0.6843
0.5819
3.0
8527
0.5815
0.6855
0.5768
4.0
11368
0.5816
0.6842
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu117
Datasets 2.18.0
Tokenizers 0.13.3
