Downloads · 30 days
2
3% of all-time downloads
nl2vis-chart-flan-t5-base
2024aa05350saurabh/nl2vis-chart-flan-t5-base
nl2vis-chart-flan-t5-base is a machine learning model from 2024aa05350saurabh. 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
76
Public
Parameters
248M
5 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors990 MB · 100%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Jun 12, 2026
- Updated
- Jun 13, 2026
- SHA
- 9009f346
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. -->
nl2vis-chart-flan-t5-base
This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0012
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: 0.0003
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 300
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.4146 | 0.2066 | 500 | 0.0280 |
| 0.1956 | 0.4133 | 1000 | 0.0154 |
| 0.1353 | 0.6199 | 1500 | 0.0097 |
| 0.1411 | 0.8266 | 2000 | 0.0080 |
| 0.1098 | 1.0331 | 2500 | 0.0067 |
| 0.0993 | 1.2397 | 3000 | 0.0050 |
| 0.0818 | 1.4464 | 3500 | 0.0037 |
| 0.0726 | 1.6530 | 4000 | 0.0044 |
| 0.0676 | 1.8596 | 4500 | 0.0037 |
| 0.0578 | 2.0661 | 5000 | 0.0029 |
| 0.0316 | 2.2728 | 5500 | 0.0022 |
| 0.0267 | 2.4794 | 6000 | 0.0031 |
| 0.0205 | 2.6861 | 6500 | 0.0019 |
| 0.0263 | 2.8927 | 7000 | 0.0013 |
| 0.0181 | 3.0992 | 7500 | 0.0013 |
| 0.0093 | 3.3058 | 8000 | 0.0015 |
| 0.0062 | 3.5125 | 8500 | 0.0015 |
| 0.0091 | 3.7191 | 9000 | 0.0014 |
| 0.0100 | 3.9258 | 9500 | 0.0012 |
| 0.0133 | 4.1323 | 10000 | 0.0013 |
| 0.0088 | 4.3389 | 10500 | 0.0012 |
| 0.0102 | 4.5455 | 11000 | 0.0012 |
| 0.0074 | 4.7522 | 11500 | 0.0012 |
| 0.0053 | 4.9588 | 12000 | 0.0012 |
| 0.0086 | 5.0 | 12100 | 0.0012 |
Framework versions
- Transformers 5.12.0
- Pytorch 2.11.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Jun 12, 2026
- Updated
- Jun 13, 2026