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t5-conversation-summ-rust
mdizak/t5-conversation-summ-rust
t5-conversation-summ-rust is a machine learning model from mdizak. 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. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- bart
- Access
- Public
- Created
- Mar 31, 2024
- Updated
- Mar 31, 2024
- SHA
- 0ef8c1ed
Base models
Datasets
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. -->
t5-conversation-summ
This model is a fine-tuned version of facebook/bart-large-xsum on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 0.3003
- Rouge1: 54.4662
- Rouge2: 29.9033
- Rougel: 44.7615
- Rougelsum: 50.1037
- Gen Len: 29.4487
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.2898 | 1.0 | 3683 | 0.3003 | 54.4662 | 29.9033 | 44.7615 | 50.1037 | 29.4487 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
- Library
- transformers
- Type
- bart
- License
- mit
- Created
- Mar 31, 2024
- Updated
- Mar 31, 2024