Downloads · 30 days
8
29% of all-time downloads
HAR_model
Yuss68/HAR_model
HAR_model is a machine learning model from Yuss68. 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
60.5M
243 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors242 MB · 99%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Feb 15, 2024
- Updated
- Feb 15, 2024
- SHA
- f99e4640
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. -->
HAR_model
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.5524
- Rouge1: 0.3529
- Rouge2: 0.1071
- Rougel: 0.2263
- Rougelsum: 0.2263
- Gen Len: 86.0
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 1 | 2.9579 | 0.312 | 0.0738 | 0.2003 | 0.2003 | 75.0 |
| No log | 2.0 | 2 | 2.8855 | 0.312 | 0.0738 | 0.2003 | 0.2003 | 75.0 |
| No log | 3.0 | 3 | 2.8381 | 0.3376 | 0.0808 | 0.205 | 0.205 | 77.5 |
| No log | 4.0 | 4 | 2.7929 | 0.3383 | 0.0903 | 0.2018 | 0.2018 | 74.5 |
| No log | 5.0 | 5 | 2.7389 | 0.3383 | 0.0903 | 0.2018 | 0.2018 | 74.5 |
| No log | 6.0 | 6 | 2.6640 | 0.3383 | 0.0903 | 0.2018 | 0.2018 | 74.5 |
| No log | 7.0 | 7 | 2.6333 | 0.3422 | 0.0916 | 0.1961 | 0.1961 | 72.0 |
| No log | 8.0 | 8 | 2.6110 | 0.3383 | 0.0903 | 0.2018 | 0.2018 | 74.5 |
| No log | 9.0 | 9 | 2.5951 | 0.3529 | 0.1071 | 0.2263 | 0.2263 | 86.0 |
| No log | 10.0 | 10 | 2.5826 | 0.3529 | 0.1071 | 0.2263 | 0.2263 | 86.0 |
| No log | 11.0 | 11 | 2.5732 | 0.3529 | 0.1071 | 0.2263 | 0.2263 | 86.0 |
| No log | 12.0 | 12 | 2.5632 | 0.3529 | 0.1071 | 0.2263 | 0.2263 | 86.0 |
| No log | 13.0 | 13 | 2.5632 | 0.3529 | 0.1071 | 0.2263 | 0.2263 | 86.0 |
| No log | 14.0 | 14 | 2.5562 | 0.3529 | 0.1071 | 0.2263 | 0.2263 | 86.0 |
| No log | 15.0 | 15 | 2.5524 | 0.3529 | 0.1071 | 0.2263 | 0.2263 | 86.0 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Feb 15, 2024
- Updated
- Feb 15, 2024