Downloads · 30 days
10
21% of all-time downloads
model_v1_complete_training_wt_init_48_small_emb_comp
gokuls/model_v1_complete_training_wt_init_48_small_emb_comp
model_v1_complete_training_wt_init_48_small_emb_comp is a fill-mask model from gokuls. Use it when you need the model to fill a missing word. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
48
Public
Repo size
1.5 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin73.4 MB · 98%
At a glance
- Task
- Fill-Mask
- Library
- transformers
- Model type
- hybridbert
- Access
- Public
- Created
- Jul 17, 2023
- Updated
- Jul 18, 2023
- SHA
- 625de64c
Try a prompt
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_v1_complete_training_wt_init_48_small_emb_comp
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.3637
- Accuracy: 0.2281
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: 1e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 6.5703 | 0.25 | 30000 | 6.5612 | 0.1162 |
| 6.3542 | 0.49 | 60000 | 6.3484 | 0.1335 |
| 6.2455 | 0.74 | 90000 | 6.2454 | 0.1406 |
| 6.1931 | 0.98 | 120000 | 6.1884 | 0.1438 |
| 6.1452 | 1.23 | 150000 | 6.1441 | 0.1460 |
| 6.1194 | 1.47 | 180000 | 6.1122 | 0.1481 |
| 6.0939 | 1.72 | 210000 | 6.0831 | 0.1488 |
| 6.0463 | 1.97 | 240000 | 6.0348 | 0.1504 |
| 6.0078 | 2.21 | 270000 | 6.0020 | 0.1516 |
| 5.9732 | 2.46 | 300000 | 5.9705 | 0.1531 |
| 5.9408 | 2.7 | 330000 | 5.9340 | 0.1542 |
| 5.9028 | 2.95 | 360000 | 5.8904 | 0.1567 |
| 5.8675 | 3.2 | 390000 | 5.8527 | 0.1597 |
| 5.8365 | 3.44 | 420000 | 5.8116 | 0.1655 |
| 5.7944 | 3.69 | 450000 | 5.7580 | 0.1753 |
| 5.7198 | 3.93 | 480000 | 5.6695 | 0.1896 |
| 5.6264 | 4.18 | 510000 | 5.5688 | 0.2028 |
| 5.5337 | 4.42 | 540000 | 5.4742 | 0.2137 |
| 5.4748 | 4.67 | 570000 | 5.4033 | 0.2228 |
| 5.4301 | 4.92 | 600000 | 5.3637 | 0.2281 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Fill-Mask
- Library
- transformers
- Type
- hybridbert
- Created
- Jul 17, 2023
- Updated
- Jul 18, 2023