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---
base_model: ccdv/lsg-bart-base-16384-pubmed
tags:
- generated_from_trainer
datasets:
- pubmed-summarization
model-index:
- name: lsg-bart-base-16384-pubmed-finetuned-pubmed-16394
results: []
---
<!-- 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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/thanhkt27507-vsu/huggingface/runs/056l8muj)
# lsg-bart-base-16384-pubmed-finetuned-pubmed-16394
This model is a fine-tuned version of [ccdv/lsg-bart-base-16384-pubmed](https://huggingface.co/ccdv/lsg-bart-base-16384-pubmed) on the pubmed-summarization dataset.
It achieves the following results on the evaluation set:
- eval_loss: 5.6482
- eval_rouge1: 0.451
- eval_rouge2: 0.2128
- eval_rougeL: 0.2772
- eval_rougeLsum: 0.4174
- eval_runtime: 484.657
- eval_samples_per_second: 0.413
- eval_steps_per_second: 0.206
- epoch: 1.6
- step: 100
## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 9
### Framework versions
- Transformers 4.42.4
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.19.1
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