bart-samsum2 / README.md
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---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: rlqaf
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
config: samsum
split: validation
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 0.4864
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# rlqaf
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5315
- Rouge1: 0.4864
- Rouge2: 0.2554
- Rougel: 0.4099
- Rougelsum: 0.4099
- Gen Len: 18.2457
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.5336 | 4.34 | 500 | 0.5418 | 0.4838 | 0.2529 | 0.4106 | 0.4104 | 18.2751 |
| 0.4117 | 8.69 | 1000 | 0.5315 | 0.4864 | 0.2554 | 0.4099 | 0.4099 | 18.2457 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0