Downloads · 30 days
21
26% of all-time downloads
mt5-small-finetuned-gec-0.2
smartik/mt5-small-finetuned-gec-0.2
mt5-small-finetuned-gec-0.2 is a machine learning model from smartik. 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
80
Public
Repo size
12 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.2 GB · 98%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- mt5
- Access
- Public
- Created
- Mar 4, 2023
- Updated
- Mar 5, 2023
- SHA
- 4e41e7c1
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. -->
mt5-small-finetuned-gec-0.2
This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6969
- Rouge1: 19.1064
- Rouge2: 6.4052
- Rougel: 19.1295
- Rougelsum: 19.214
- Gen Len: 29.7537
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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.2261 | 1.0 | 4092 | 0.6969 | 19.1064 | 6.4052 | 19.1295 | 19.214 | 29.7537 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
- Library
- transformers
- Type
- mt5
- License
- apache-2.0
- Created
- Mar 4, 2023
- Updated
- Mar 5, 2023