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M4-chunk-300 – AI Model by raminass | AlphaNeural AI
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raminass
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M4-chunk-300
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tensorboard
safetensors
bert
generated_from_trainer
raminass/scotus-v10
finetune
cc-by-sa-4.0
us
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M4-chunk-300
This model is a fine-tuned version of
raminass/scotus-v10
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.9865
Accuracy: 0.7412
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-05
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.698
1.0
2994
0.9606
0.7182
0.3583
2.0
5988
0.9809
0.7295
0.2108
3.0
8982
0.9865
0.7412
Framework versions
Transformers 4.38.0
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.15.2
