Summarization
Transformers
PyTorch
TensorBoard
Swedish
bart
text2text-generation
Eval Results (legacy)
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Gabriel/bart-base-cnn-xsum-swe")
model = AutoModelForSeq2SeqLM.from_pretrained("Gabriel/bart-base-cnn-xsum-swe")Quick Links
bart-base-cnn-xsum-swe
This model is a fine-tuned version of Gabriel/bart-base-cnn-swe on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.1027
- Rouge1: 30.9467
- Rouge2: 12.2589
- Rougel: 25.4487
- Rougelsum: 25.4792
- Gen Len: 19.7379
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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.3076 | 1.0 | 6375 | 2.1986 | 29.7041 | 10.9883 | 24.2149 | 24.2406 | 19.7193 |
| 2.0733 | 2.0 | 12750 | 2.1246 | 30.4521 | 11.8107 | 24.9519 | 24.9745 | 19.6592 |
| 1.8933 | 3.0 | 19125 | 2.0989 | 30.9407 | 12.2682 | 25.4135 | 25.4378 | 19.7195 |
| 1.777 | 4.0 | 25500 | 2.1027 | 30.9467 | 12.2589 | 25.4487 | 25.4792 | 19.7379 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1
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Dataset used to train Gabriel/bart-base-cnn-xsum-swe
Space using Gabriel/bart-base-cnn-xsum-swe 1
Evaluation results
- Validation ROGUE-1. on Gabriel/xsum_swevalidation set self-reported30.947
- Validation ROGUE-2 on Gabriel/xsum_swevalidation set self-reported12.259
- Validation ROGUE-L on Gabriel/xsum_swevalidation set self-reported25.449
- Validation ROGUE-L-SUM on Gabriel/xsum_swevalidation set self-reported25.479
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("summarization", model="Gabriel/bart-base-cnn-xsum-swe")