bart-base-xsum
Training: The model has been trained using the script provided in the following repository https://github.com/MorenoLaQuatra/transformers-tasks-templates
This model is a fine-tuned version of facebook/bart-base on xsum dataset. It achieves the following results on the evaluation set:
- Loss: 0.8051
- R1: 0.5643
- R2: 0.3017
- Rl: 0.5427
- Rlsum: 0.5427
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: 32
- eval_batch_size: 32
- seed: 42
- 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 | R1 | R2 | Rl | Rlsum |
---|---|---|---|---|---|---|---|
0.8983 | 1.0 | 6377 | 0.8145 | 0.5443 | 0.2724 | 0.5212 | 0.5211 |
0.8211 | 2.0 | 12754 | 0.7940 | 0.5519 | 0.2831 | 0.5295 | 0.5295 |
0.7701 | 3.0 | 19131 | 0.7839 | 0.5569 | 0.2896 | 0.5347 | 0.5348 |
0.7046 | 4.0 | 25508 | 0.7792 | 0.5615 | 0.2956 | 0.5394 | 0.5393 |
0.6837 | 5.0 | 31885 | 0.7806 | 0.5631 | 0.2993 | 0.5416 | 0.5416 |
0.6412 | 6.0 | 38262 | 0.7816 | 0.5643 | 0.301 | 0.5427 | 0.5426 |
0.6113 | 7.0 | 44639 | 0.7881 | 0.5645 | 0.3017 | 0.5428 | 0.5428 |
0.5855 | 8.0 | 51016 | 0.7921 | 0.5651 | 0.303 | 0.5433 | 0.5432 |
0.5636 | 9.0 | 57393 | 0.7972 | 0.5649 | 0.3032 | 0.5433 | 0.5433 |
0.5482 | 10.0 | 63770 | 0.7996 | 0.565 | 0.3036 | 0.5436 | 0.5435 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.11.0+cu113
- Datasets 2.0.0
- Tokenizers 0.11.6
- Downloads last month
- 29
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for morenolq/bart-base-xsum
Base model
facebook/bart-base
Finetuned
this model
Evaluation results
- ROUGE-1 on xsumtest set verified38.651
- ROUGE-2 on xsumtest set verified17.759
- ROUGE-L on xsumtest set verified32.203
- ROUGE-LSUM on xsumtest set verified32.206
- loss on xsumtest set verified1.822
- gen_len on xsumtest set verified19.703
- ROUGE-1 on xsumvalidation set verified38.742
- ROUGE-2 on xsumvalidation set verified17.829
- ROUGE-L on xsumvalidation set verified32.286
- ROUGE-LSUM on xsumvalidation set verified32.276