Edit model card

bart-abs-2409-1947-lr-3e-06-bs-8-maxep-10

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-6 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 7.8363
  • Rouge/rouge1: 0.3097
  • Rouge/rouge2: 0.0856
  • Rouge/rougel: 0.2463
  • Rouge/rougelsum: 0.2464
  • Bertscore/bertscore-precision: 0.8589
  • Bertscore/bertscore-recall: 0.8656
  • Bertscore/bertscore-f1: 0.8622
  • Meteor: 0.2246
  • Gen Len: 36.0

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: 3e-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge/rouge1 Rouge/rouge2 Rouge/rougel Rouge/rougelsum Bertscore/bertscore-precision Bertscore/bertscore-recall Bertscore/bertscore-f1 Meteor Gen Len
0.1784 1.0 109 7.8164 0.3097 0.0856 0.2463 0.2464 0.8589 0.8656 0.8622 0.2246 36.0
0.1816 2.0 218 7.8349 0.2722 0.0714 0.2029 0.2031 0.8612 0.8618 0.8615 0.2582 44.0
0.1813 3.0 327 7.8471 0.2677 0.0541 0.2002 0.2007 0.8757 0.864 0.8697 0.25 37.0
0.1798 4.0 436 7.8598 0.3097 0.0856 0.2463 0.2464 0.8589 0.8656 0.8622 0.2246 36.0
0.2 5.0 545 7.8568 0.2722 0.0714 0.2029 0.2031 0.8612 0.8618 0.8615 0.2582 44.0
0.2047 6.0 654 7.8458 0.3097 0.0856 0.2463 0.2464 0.8589 0.8656 0.8622 0.2246 36.0
0.2066 7.0 763 7.8409 0.3097 0.0856 0.2463 0.2464 0.8589 0.8656 0.8622 0.2246 36.0
0.2144 8.0 872 7.8382 0.2646 0.0434 0.203 0.2031 0.867 0.8616 0.8642 0.2187 36.0
0.2062 9.0 981 7.8368 0.2646 0.0434 0.203 0.2031 0.867 0.8616 0.8642 0.2187 36.0
0.2056 10.0 1090 7.8363 0.3097 0.0856 0.2463 0.2464 0.8589 0.8656 0.8622 0.2246 36.0

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0
  • Datasets 3.0.0
  • Tokenizers 0.19.1
Downloads last month
2
Safetensors
Model size
306M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for roequitz/bart-abs-2409-1947-lr-3e-06-bs-8-maxep-10

Finetuned
(43)
this model