Downloads · 30 days
24
1% of all-time downloads
t5-small-finetuned-spider
tomhavy/t5-small-finetuned-spider
t5-small-finetuned-spider is a machine learning model from tomhavy. 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.
should probably proofread and complete it, then remove this comment. --
All-time downloads
3.4K
Public
Repo size
1.9 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin242 MB · 99%
At a glance
- Library
- transformers
- Model type
- t5
- Access
- Public
- Created
- May 13, 2022
- Updated
- May 13, 2022
- SHA
- 737f58ee
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. -->
t5-small-finetuned-spider
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1914
- Rouge2 Precision: 0.6349
- Rouge2 Recall: 0.3964
- Rouge2 Fmeasure: 0.4619
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: 5e-05
- train_batch_size: 5
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.2912 | 1.0 | 1120 | 0.2631 | 0.5653 | 0.3537 | 0.4118 |
| 0.2967 | 2.0 | 2240 | 0.2465 | 0.5758 | 0.363 | 0.4209 |
| 0.3106 | 3.0 | 3360 | 0.2372 | 0.5858 | 0.367 | 0.427 |
| 0.2993 | 4.0 | 4480 | 0.2340 | 0.5995 | 0.3791 | 0.4403 |
| 0.2702 | 5.0 | 5600 | 0.2204 | 0.6035 | 0.3786 | 0.4401 |
| 0.2624 | 6.0 | 6720 | 0.2159 | 0.6094 | 0.3807 | 0.4435 |
| 0.2463 | 7.0 | 7840 | 0.2121 | 0.6207 | 0.3911 | 0.4544 |
| 0.2427 | 8.0 | 8960 | 0.2053 | 0.6198 | 0.3886 | 0.452 |
| 0.2336 | 9.0 | 10080 | 0.2014 | 0.6217 | 0.3871 | 0.4518 |
| 0.2256 | 10.0 | 11200 | 0.1980 | 0.6298 | 0.394 | 0.4589 |
| 0.2212 | 11.0 | 12320 | 0.1960 | 0.6304 | 0.3936 | 0.4589 |
| 0.2141 | 12.0 | 13440 | 0.1962 | 0.63 | 0.3939 | 0.4586 |
| 0.2069 | 13.0 | 14560 | 0.1921 | 0.6328 | 0.3942 | 0.4594 |
| 0.2096 | 14.0 | 15680 | 0.1915 | 0.632 | 0.3953 | 0.46 |
| 0.2115 | 15.0 | 16800 | 0.1914 | 0.6349 | 0.3964 | 0.4619 |
Framework versions
- Transformers 4.19.0
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1
- Library
- transformers
- Type
- t5
- Created
- May 13, 2022
- Updated
- May 13, 2022