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mbart-large-50-finetuned-summarization-V2
GiordanoB/mbart-large-50-finetuned-summarization-V2
mbart-large-50-finetuned-summarization-V2 is a machine learning model from GiordanoB. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- mbart
- Access
- Public
- Created
- May 28, 2022
- Updated
- May 29, 2022
- SHA
- 9c32cdb2
Model card
From the Hugging Face model README
<!-- 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. -->
mbart-large-50-finetuned-summarization-V2
This model is a fine-tuned version of facebook/mbart-large-50 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9183
- Rouge1: 50.0118
- Rouge2: 31.3168
- Rougel: 37.6392
- Rougelsum: 45.2287
- Gen Len: 102.3571
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 15 | 2.0228 | 51.9711 | 32.5963 | 39.9154 | 48.3431 | 134.6429 |
| No log | 2.0 | 30 | 1.9410 | 48.2977 | 30.5942 | 35.9761 | 43.7634 | 92.0714 |
| No log | 3.0 | 45 | 1.9183 | 50.0118 | 31.3168 | 37.6392 | 45.2287 | 102.3571 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
- Library
- transformers
- Type
- mbart
- Created
- May 28, 2022
- Updated
- May 29, 2022