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flan-t5-small-finetuned-Coca
LeoR2/flan-t5-small-finetuned-Coca
flan-t5-small-finetuned-Coca is a machine learning model from LeoR2. 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Nov 16, 2023
- Updated
- Nov 17, 2023
- SHA
- 60ca518c
Base models
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. -->
flan-t5-small-finetuned-Coca
This model is a fine-tuned version of google/flan-t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 35.8419
- Rouge2: 14.1387
- Rougel: 29.6846
- Rougelsum: 29.7698
- Gen Len: 17.0846
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: 1e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 101 | nan | 35.8419 | 14.1387 | 29.6846 | 29.7698 | 17.0846 |
| No log | 2.0 | 202 | nan | 35.8419 | 14.1387 | 29.6846 | 29.7698 | 17.0846 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Nov 16, 2023
- Updated
- Nov 17, 2023