Downloads · 30 days
5
18% of all-time downloads
t-5_base_extractive_512_750
jgibb/t-5_base_extractive_512_750
t-5_base_extractive_512_750 is a machine learning model from jgibb. 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. --
All-time downloads
28
Public
Parameters
223M
892 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors892 MB · 100%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Mar 17, 2024
- Updated
- Mar 17, 2024
- SHA
- 00793758
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. -->
t-5_base_extractive_512_750
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2627
- Rouge1: 0.6597
- Rouge2: 0.3836
- Rougel: 0.5954
- Rougelsum: 0.5953
- Wer: 0.5117
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: 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: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Wer |
|---|---|---|---|---|---|---|---|---|
| No log | 0.13 | 250 | 1.3741 | 0.6424 | 0.3616 | 0.5756 | 0.5756 | 0.5348 |
| 1.8339 | 0.27 | 500 | 1.3204 | 0.6501 | 0.371 | 0.5847 | 0.5847 | 0.5245 |
| 1.8339 | 0.4 | 750 | 1.2968 | 0.6533 | 0.3761 | 0.5886 | 0.5885 | 0.5192 |
| 1.4045 | 0.53 | 1000 | 1.2796 | 0.6568 | 0.3798 | 0.5919 | 0.5918 | 0.5161 |
| 1.4045 | 0.66 | 1250 | 1.2723 | 0.6582 | 0.382 | 0.5938 | 0.5937 | 0.5134 |
| 1.3616 | 0.8 | 1500 | 1.2656 | 0.659 | 0.3833 | 0.5947 | 0.5947 | 0.5122 |
| 1.3616 | 0.93 | 1750 | 1.2627 | 0.6597 | 0.3836 | 0.5954 | 0.5953 | 0.5117 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Mar 17, 2024
- Updated
- Mar 17, 2024