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inetuned-summarize-test
minnehwg/inetuned-summarize-test
inetuned-summarize-test is a machine learning model from minnehwg. 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
- t5
- Access
- Public
- Created
- May 10, 2024
- Updated
- May 11, 2024
- SHA
- c478054a
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. -->
inetuned-summarize-test
This model is a fine-tuned version of minnehwg/inetuned-summarize-test on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8961
- Rouge1: 34.2527
- Rouge2: 14.2278
- Rougel: 24.7229
- Rougelsum: 25.3930
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 250 | 0.9249 | 34.2996 | 13.7194 | 24.5150 | 25.1146 |
| 0.6471 | 2.0 | 500 | 0.9104 | 34.1716 | 14.0356 | 24.6683 | 25.1958 |
| 0.6471 | 3.0 | 750 | 0.8961 | 34.2527 | 14.2278 | 24.7229 | 25.3930 |
Framework versions
- Transformers 4.17.0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- t5
- License
- mit
- Created
- May 10, 2024
- Updated
- May 11, 2024