ml_sum_v3 / README.md
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metadata
license: apache-2.0
base_model: mHossain/ml_sum_v2
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: ml_sum_v3
    results: []

ml_sum_v3

This model is a fine-tuned version of mHossain/ml_sum_v2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: nan
  • Rouge1: 0.0
  • Rouge2: 0.0
  • Rougel: 0.0
  • Rougelsum: 0.0
  • Gen Len: 0.0

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • 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: 5000
  • num_epochs: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 312 0.3728 0.0844 0.0536 0.0844 0.0844 19.0
0.4276 2.0 625 0.3728 0.0844 0.0536 0.0844 0.0844 19.0
0.4276 3.0 937 nan 0.0 0.0 0.0 0.0 0.0
0.7627 3.99 1248 nan 0.0 0.0 0.0 0.0 0.0

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2