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muril-base-cased-finetuned-non-code-mixed-DS
IIIT-L/muril-base-cased-finetuned-non-code-mixed-DS
muril-base-cased-finetuned-non-code-mixed-DS is a text classification model from IIIT-L. Use it when you need a label for a piece of text. 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. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Sep 29, 2022
- Updated
- Sep 29, 2022
- SHA
- cedce4aa
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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. -->
muril-base-cased-finetuned-non-code-mixed-DS
This model is a fine-tuned version of google/muril-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2867
- Accuracy: 0.6214
- Precision: 0.6081
- Recall: 0.6009
- F1: 0.6034
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: 32
- eval_batch_size: 32
- seed: 43
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.0861 | 2.0 | 463 | 1.0531 | 0.3506 | 0.1169 | 0.3333 | 0.1731 |
| 0.99 | 3.99 | 926 | 0.9271 | 0.5836 | 0.4310 | 0.5200 | 0.4502 |
| 0.8759 | 5.99 | 1389 | 0.9142 | 0.5965 | 0.5788 | 0.5907 | 0.5802 |
| 0.7726 | 7.98 | 1852 | 0.8726 | 0.6095 | 0.6079 | 0.6078 | 0.6027 |
| 0.6659 | 9.98 | 2315 | 0.9145 | 0.6246 | 0.6139 | 0.6174 | 0.6140 |
| 0.5727 | 11.97 | 2778 | 0.9606 | 0.6311 | 0.6180 | 0.6109 | 0.6133 |
| 0.4889 | 13.97 | 3241 | 1.0342 | 0.6170 | 0.6059 | 0.6054 | 0.6045 |
| 0.4267 | 15.97 | 3704 | 1.0539 | 0.6170 | 0.6089 | 0.6081 | 0.6066 |
| 0.3751 | 17.96 | 4167 | 1.1740 | 0.6343 | 0.6255 | 0.6074 | 0.6112 |
| 0.3402 | 19.96 | 4630 | 1.2021 | 0.6192 | 0.6078 | 0.6013 | 0.6031 |
| 0.318 | 21.95 | 5093 | 1.2875 | 0.6181 | 0.6007 | 0.5946 | 0.5965 |
| 0.2977 | 23.95 | 5556 | 1.2867 | 0.6214 | 0.6081 | 0.6009 | 0.6034 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Sep 29, 2022
- Updated
- Sep 29, 2022