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1m-model

This model is a fine-tuned version of eslamxm/MBart-finetuned-ur-xlsum on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5999

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: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
0.862 0.1 500 0.7994
0.7785 0.2 1000 0.7464
0.7568 0.3 1500 0.7119
0.6927 0.4 2000 0.6837
0.7486 0.49 2500 0.6636
0.7208 0.59 3000 0.6463
0.6784 0.69 3500 0.6297
0.6286 0.79 4000 0.6166
0.6339 0.89 4500 0.6063
0.6738 0.99 5000 0.5999

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.15.0
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Model size
611M params
Tensor type
F32
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Finetuned from