fine-tuned-BioBART-10-epochs

This model is a fine-tuned version of GanjinZero/biobart-v2-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7099
  • Rouge1: 0.2929
  • Rouge2: 0.1172
  • Rougel: 0.2685
  • Rougelsum: 0.2674
  • Gen Len: 14.66

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
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 151 0.7536 0.204 0.0789 0.1879 0.1874 13.31
No log 2.0 302 0.7161 0.2576 0.0833 0.2281 0.227 13.88
No log 3.0 453 0.7013 0.2314 0.082 0.2052 0.2053 14.57
0.7283 4.0 604 0.6976 0.2835 0.1092 0.2574 0.2572 14.34
0.7283 5.0 755 0.7012 0.2761 0.0916 0.252 0.2525 14.35
0.7283 6.0 906 0.6963 0.2959 0.108 0.2692 0.2692 14.97
0.5246 7.0 1057 0.7043 0.2848 0.1074 0.2558 0.2563 14.68
0.5246 8.0 1208 0.7043 0.2945 0.1168 0.271 0.2701 14.16
0.5246 9.0 1359 0.7080 0.2875 0.1097 0.2604 0.2598 14.69
0.4414 10.0 1510 0.7099 0.2929 0.1172 0.2685 0.2674 14.66

Framework versions

  • Transformers 4.36.2
  • Pytorch 1.12.1+cu113
  • Datasets 2.15.0
  • Tokenizers 0.15.0
Downloads last month
10
Safetensors
Model size
166M 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 tanatapanun/fine-tuned-BioBART-10-epochs

Finetuned
(13)
this model