metadata
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: bert_large_xsum_samsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
config: samsum
split: test
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 0.5083
bert_large_xsum_samsum
This model is a fine-tuned version of facebook/bart-large-xsum on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.9030
- Rouge1: 0.5083
- Rouge2: 0.2528
- Rougel: 0.41
- Rougelsum: 0.4105
- Gen Len: 29.0183
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 41 | 1.6008 | 0.4779 | 0.2349 | 0.4058 | 0.4056 | 21.1037 |
| No log | 2.0 | 82 | 1.5804 | 0.5104 | 0.2526 | 0.4242 | 0.4239 | 24.689 |
| No log | 3.0 | 123 | 1.7310 | 0.5148 | 0.253 | 0.4162 | 0.4155 | 28.0793 |
| No log | 4.0 | 164 | 1.7974 | 0.5019 | 0.2443 | 0.4127 | 0.4125 | 25.189 |
| No log | 5.0 | 205 | 1.9030 | 0.5083 | 0.2528 | 0.41 | 0.4105 | 29.0183 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1