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Text_Summarization_model_15042024
vishnun0027/Text_Summarization_model_15042024
Text_Summarization_model_15042024 is a machine learning model from vishnun0027. 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
- Apr 15, 2024
- Updated
- Apr 15, 2024
- SHA
- fbf77e9a
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. -->
Text_Summarization_model_15042024
This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5948
- Rouge1: 0.2374
- Rouge2: 0.1905
- Rougel: 0.2302
- Rougelsum: 0.2302
- Gen Len: 19.0
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: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.4344 | 0.5 | 500 | 1.9250 | 0.2184 | 0.1678 | 0.2088 | 0.2088 | 18.9925 |
| 2.0598 | 1.0 | 1000 | 1.8118 | 0.2247 | 0.1755 | 0.2155 | 0.2155 | 18.9955 |
| 1.9648 | 1.5 | 1500 | 1.7581 | 0.2303 | 0.1802 | 0.2206 | 0.2206 | 19.0 |
| 1.9119 | 2.0 | 2000 | 1.7214 | 0.2315 | 0.1822 | 0.2221 | 0.2221 | 19.0 |
| 1.8624 | 2.5 | 2500 | 1.6953 | 0.2337 | 0.185 | 0.2253 | 0.2253 | 19.0 |
| 1.8508 | 3.0 | 3000 | 1.6769 | 0.2346 | 0.186 | 0.2266 | 0.2266 | 19.0 |
| 1.8092 | 3.5 | 3500 | 1.6563 | 0.2353 | 0.1871 | 0.2278 | 0.2279 | 19.0 |
| 1.8065 | 4.0 | 4000 | 1.6377 | 0.2359 | 0.188 | 0.2284 | 0.2284 | 19.0 |
| 1.7724 | 4.5 | 4500 | 1.6309 | 0.237 | 0.1895 | 0.2297 | 0.2298 | 19.0 |
| 1.7703 | 5.0 | 5000 | 1.6165 | 0.2376 | 0.1899 | 0.2302 | 0.2303 | 19.0 |
| 1.7468 | 5.5 | 5500 | 1.6082 | 0.2374 | 0.1902 | 0.2303 | 0.2303 | 19.0 |
| 1.7347 | 6.0 | 6000 | 1.5992 | 0.2374 | 0.1906 | 0.2303 | 0.2304 | 19.0 |
| 1.7162 | 6.5 | 6500 | 1.5948 | 0.2374 | 0.1905 | 0.2302 | 0.2302 | 19.0 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Apr 15, 2024
- Updated
- Apr 15, 2024