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bart_base_xsum_20k – AI Model by Rythmbounvy | AlphaNeural AI
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bart_base_xsum_20k
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transformers
safetensors
bart
text2text-generation
generated_from_trainer
xsum
facebook/bart-base
finetune
apache-2.0
endpoints_compatible
us
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bart_base_xsum_20k
This model is a fine-tuned version of
facebook/bart-base
on the xsum dataset. It achieves the following results on the evaluation set:
Loss: 0.9033
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: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.7374
1.0
1276
0.9033
Framework versions
Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2
