metadata
library_name: transformers
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-pbmed-hierarchicall
results: []
bart-pbmed-hierarchicall
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: 3.3741
- Rouge1: 23.99
- Rouge2: 3.43
- Rougel: 15.21
- Rougelsum: 21.93
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 3.9967 | 0.2668 | 200 | 3.6014 | 0.0 | 0.0 | 0.0 | 0.0 |
| 3.8428 | 0.5337 | 400 | 3.4873 | 23.23 | 3.18 | 15.17 | 21.08 |
| 3.7321 | 0.8005 | 600 | 3.4202 | 23.41 | 3.18 | 14.28 | 21.41 |
| 3.6064 | 1.0674 | 800 | 3.3899 | 0.0 | 0.0 | 0.0 | 0.0 |
| 3.5746 | 1.3342 | 1000 | 3.3741 | 23.99 | 3.43 | 15.21 | 21.93 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1