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satire-sft-bart_training_truncated_weighted – AI Model by narwhalsilent | AlphaNeural AI
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satire-sft-bart_training_truncated_weighted
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transformers
safetensors
bart
text2text-generation
generated_from_trainer
facebook/bart-base
finetune
apache-2.0
endpoints_compatible
us
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satire-sft-bart_training_truncated_weighted
This model is a fine-tuned version of
facebook/bart-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 2.4363
Rouge1: 0.4115
Rouge2: 0.199
Rougel: 0.3752
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: 16
eval_batch_size: 64
seed: 42
distributed_type: multi-GPU
num_devices: 2
total_train_batch_size: 32
total_eval_batch_size: 128
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 218
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
3.0739
1.0
438
2.5732
0.4161
0.1999
0.3812
2.7548
2.0
876
2.4794
0.4075
0.1943
0.3714
2.5138
3.0
1314
2.4363
0.4115
0.199
0.3752
Framework versions
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.8.3
Tokenizers 0.22.2
