Downloads · 30 days
2
17% of all-time downloads
model_output
arpit-sri/model_output
model_output is a machine learning model from arpit-sri. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
12
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
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Sep 1, 2024
- Updated
- Sep 1, 2024
- SHA
- 10c722f5
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. -->
model_output
This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8702
- Rouge-1: {'r': 0.1449206060602415, 'p': 0.612228865799888, 'f': 0.2314199657444668}
- Rouge-2: {'r': 0.06217585891598185, 'p': 0.3306214679875187, 'f': 0.10338896078492887}
- Rouge-l: {'r': 0.12714023830372423, 'p': 0.539238202328148, 'f': 0.20314789762608454}
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
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l |
|---|---|---|---|---|---|---|
| 2.2905 | 1.0 | 774 | 1.9726 | {'r': 0.14027789446494138, 'p': 0.6013831620449274, 'f': 0.22452882138970473} | {'r': 0.05888226359145526, 'p': 0.31779608267296355, 'f': 0.09805637819321582} | {'r': 0.1224534604628376, 'p': 0.5254403024438363, 'f': 0.19599547417477767} |
| 2.0699 | 2.0 | 1548 | 1.9046 | {'r': 0.1443383469259305, 'p': 0.6126968055462134, 'f': 0.23058379100363557} | {'r': 0.061031058218561175, 'p': 0.3258341532224339, 'f': 0.10151469929542385} | {'r': 0.12661559647672582, 'p': 0.5387896667222934, 'f': 0.20232290318208698} |
| 2.0266 | 3.0 | 2322 | 1.8790 | {'r': 0.14521947151897238, 'p': 0.6137526775465678, 'f': 0.23191975811273857} | {'r': 0.062005041526819744, 'p': 0.3292476462164101, 'f': 0.10309342638663624} | {'r': 0.12726161117386992, 'p': 0.5393284920986702, 'f': 0.20331473785771298} |
| 2.0042 | 4.0 | 3096 | 1.8702 | {'r': 0.1449206060602415, 'p': 0.612228865799888, 'f': 0.2314199657444668} | {'r': 0.06217585891598185, 'p': 0.3306214679875187, 'f': 0.10338896078492887} | {'r': 0.12714023830372423, 'p': 0.539238202328148, 'f': 0.20314789762608454} |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Type
- t5
- License
- apache-2.0
- Created
- Sep 1, 2024
- Updated
- Sep 1, 2024