Downloads · 30 days
7
3% of all-time downloads
mega-base-multiple-choice-fp16-v4
Xenopilus/mega-base-multiple-choice-fp16-v4
mega-base-multiple-choice-fp16-v4 is a multiple choice model from Xenopilus. Use it for the multiple choice 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
234
Public
Parameters
7.3M
294 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors29.4 MB · 90%
At a glance
- Task
- multiple choice
- Library
- transformers
- License
- apache-2.0
- Model type
- mega
- Access
- Public
- Created
- Jan 17, 2024
- Updated
- Jan 17, 2024
- SHA
- 013167f9
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. -->
mega-base-multiple-choice-fp16-v4
This model is a fine-tuned version of mnaylor/mega-base-wikitext on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6932
- Accuracy: 0.4964
- Precision: 0.4964
- Recall: 0.5023
- F1: 0.4993
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: 1024
- eval_batch_size: 1024
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 24000
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 34 | 0.6932 | 0.4970 | 0.4971 | 0.5023 | 0.4997 |
| No log | 2.0 | 68 | 0.6932 | 0.4975 | 0.4975 | 0.5026 | 0.5001 |
| No log | 3.0 | 102 | 0.6932 | 0.4974 | 0.4974 | 0.5020 | 0.4997 |
| No log | 4.0 | 136 | 0.6932 | 0.4995 | 0.4995 | 0.5043 | 0.5019 |
| No log | 5.0 | 170 | 0.6932 | 0.4975 | 0.4975 | 0.5023 | 0.4999 |
| No log | 6.0 | 204 | 0.6932 | 0.4987 | 0.4987 | 0.5043 | 0.5015 |
| No log | 7.0 | 238 | 0.6932 | 0.4960 | 0.4961 | 0.5026 | 0.4993 |
| No log | 8.0 | 272 | 0.6932 | 0.4967 | 0.4967 | 0.5036 | 0.5002 |
| No log | 9.0 | 306 | 0.6932 | 0.4965 | 0.4966 | 0.5 | 0.4983 |
| No log | 10.0 | 340 | 0.6932 | 0.4964 | 0.4964 | 0.5023 | 0.4993 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- multiple choice
- Library
- transformers
- Type
- mega
- License
- apache-2.0
- Created
- Jan 17, 2024
- Updated
- Jan 17, 2024