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Vexemous_-_bart-base-finetuned-xsum-4bits
RichardErkhov/Vexemous_-_bart-base-finetuned-xsum-4bits
Vexemous_-_bart-base-finetuned-xsum-4bits is a text generation model from RichardErkhov. Use it when you need the model to write or continue text. It is set up for transformers.
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Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
bart-base-finetuned-xsum - bnb 4bits
- Model creator: https://huggingface.co/Vexemous/
- Original model: https://huggingface.co/Vexemous/bart-base-finetuned-xsum/
Original model description:
license: apache-2.0 base_model: facebook/bart-base tags:
- generated_from_trainer datasets:
- xsum metrics:
- rouge model-index:
- name: bart-base-finetuned-xsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
config: default
split: train[:10%]
args: default
metrics:
- name: Rouge1 type: rouge value: 35.8214 pipeline_tag: summarization
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
config: default
split: train[:10%]
args: default
metrics:
<!-- 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. -->
bart-base-finetuned-xsum
This model is a fine-tuned version of facebook/bart-base on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.9356
- Rouge1: 35.8214
- Rouge2: 14.7565
- Rougel: 29.4566
- Rougelsum: 29.4496
- Gen Len: 19.562
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: 16
- eval_batch_size: 16
- seed: 42
- 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 |
|---|---|---|---|---|---|---|---|---|
| 2.301 | 1.0 | 1148 | 1.9684 | 34.4715 | 13.6638 | 28.1147 | 28.1204 | 19.5816 |
| 2.1197 | 2.0 | 2296 | 1.9442 | 35.2502 | 14.284 | 28.8462 | 28.8384 | 19.5546 |
| 1.9804 | 3.0 | 3444 | 1.9406 | 35.7799 | 14.7422 | 29.3669 | 29.3742 | 19.5326 |
| 1.8891 | 4.0 | 4592 | 1.9349 | 35.5151 | 14.4668 | 29.0359 | 29.0484 | 19.5492 |
| 1.827 | 5.0 | 5740 | 1.9356 | 35.8214 | 14.7565 | 29.4566 | 29.4496 | 19.562 |
Framework versions
- Transformers 4.40.1
- Pytorch 1.13.1+cu117
- Datasets 2.19.0
- Tokenizers 0.19.1
- Task
- Text Generation
- Library
- transformers
- Type
- bart
- Created
- May 9, 2024
- Updated
- May 9, 2024