Downloads · 30 days
6
38% of all-time downloads
dialouge_summarization_model
RJ14/dialouge_summarization_model
dialouge_summarization_model is a machine learning model from RJ14. 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
16
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
- Sep 22, 2024
- Updated
- Sep 22, 2024
- SHA
- e20f80bc
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. -->
dialouge_summarization_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: 1.5091
- Rouge1: 0.3626
- Rouge2: 0.1277
- Rougel: 0.3026
- Rougelsum: 0.3025
- Gen Len: 18.818
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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.7341 | 1.0 | 779 | 1.6330 | 0.3367 | 0.102 | 0.2786 | 0.2784 | 18.802 |
| 1.4962 | 2.0 | 1558 | 1.5773 | 0.3461 | 0.1095 | 0.2848 | 0.2845 | 18.832 |
| 1.4727 | 3.0 | 2337 | 1.5615 | 0.3508 | 0.1169 | 0.2923 | 0.2921 | 18.786 |
| 1.4291 | 4.0 | 3116 | 1.5377 | 0.3544 | 0.1184 | 0.2945 | 0.2941 | 18.756 |
| 1.4146 | 5.0 | 3895 | 1.5317 | 0.355 | 0.1205 | 0.2955 | 0.2953 | 18.774 |
| 1.3913 | 6.0 | 4674 | 1.5183 | 0.3592 | 0.1247 | 0.3009 | 0.3007 | 18.794 |
| 1.3877 | 7.0 | 5453 | 1.5153 | 0.3611 | 0.1252 | 0.3009 | 0.3008 | 18.806 |
| 1.3744 | 8.0 | 6232 | 1.5105 | 0.3635 | 0.1284 | 0.303 | 0.3029 | 18.812 |
| 1.3627 | 9.0 | 7011 | 1.5106 | 0.3644 | 0.1291 | 0.3038 | 0.3037 | 18.824 |
| 1.3624 | 10.0 | 7790 | 1.5091 | 0.3626 | 0.1277 | 0.3026 | 0.3025 | 18.818 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Sep 22, 2024
- Updated
- Sep 22, 2024