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floor_model
rugvedabodke/floor_model
floor_model is a question answering model from rugvedabodke. Use it when the input is a question plus a passage. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Nov 30, 2023
- Updated
- Nov 30, 2023
- SHA
- b86ffb6d
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. -->
floor_model
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5275
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 2 | 7.1063 |
| No log | 2.0 | 4 | 5.9058 |
| No log | 3.0 | 6 | 5.7194 |
| No log | 4.0 | 8 | 5.4093 |
| No log | 5.0 | 10 | 5.0095 |
| No log | 6.0 | 12 | 4.6585 |
| No log | 7.0 | 14 | 4.3100 |
| No log | 8.0 | 16 | 3.7773 |
| No log | 9.0 | 18 | 3.2896 |
| No log | 10.0 | 20 | 2.8048 |
| No log | 11.0 | 22 | 2.2923 |
| No log | 12.0 | 24 | 1.7918 |
| No log | 13.0 | 26 | 1.3847 |
| No log | 14.0 | 28 | 1.0383 |
| No log | 15.0 | 30 | 0.8697 |
| No log | 16.0 | 32 | 0.7580 |
| No log | 17.0 | 34 | 0.6656 |
| No log | 18.0 | 36 | 0.6772 |
| No log | 19.0 | 38 | 0.7125 |
| No log | 20.0 | 40 | 0.6898 |
| No log | 21.0 | 42 | 0.6570 |
| No log | 22.0 | 44 | 0.6096 |
| No log | 23.0 | 46 | 0.5863 |
| No log | 24.0 | 48 | 0.6213 |
| No log | 25.0 | 50 | 0.6869 |
| No log | 26.0 | 52 | 0.6249 |
| No log | 27.0 | 54 | 0.5709 |
| No log | 28.0 | 56 | 0.5503 |
| No log | 29.0 | 58 | 0.5259 |
| No log | 30.0 | 60 | 0.4970 |
| No log | 31.0 | 62 | 0.4952 |
| No log | 32.0 | 64 | 0.4939 |
| No log | 33.0 | 66 | 0.4870 |
| No log | 34.0 | 68 | 0.4967 |
| No log | 35.0 | 70 | 0.5093 |
| No log | 36.0 | 72 | 0.5106 |
| No log | 37.0 | 74 | 0.5250 |
| No log | 38.0 | 76 | 0.5376 |
| No log | 39.0 | 78 | 0.5508 |
| No log | 40.0 | 80 | 0.5488 |
| No log | 41.0 | 82 | 0.5445 |
| No log | 42.0 | 84 | 0.5540 |
| No log | 43.0 | 86 | 0.5534 |
| No log | 44.0 | 88 | 0.5520 |
| No log | 45.0 | 90 | 0.5393 |
| No log | 46.0 | 92 | 0.5328 |
| No log | 47.0 | 94 | 0.5280 |
| No log | 48.0 | 96 | 0.5266 |
| No log | 49.0 | 98 | 0.5274 |
| No log | 50.0 | 100 | 0.5275 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Question Answering
- Library
- transformers
- Type
- distilbert
- Created
- Nov 30, 2023
- Updated
- Nov 30, 2023