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Telugu-sentiment_analysis_summaries
aashish-249/Telugu-sentiment_analysis_summaries
Telugu-sentiment_analysis_summaries is a machine learning model from aashish-249. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Nov 17, 2023
Repo size
47.5 MB
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At a glance
- License
- mit
- Access
- Public
- Created
- Nov 17, 2023
- Updated
- Nov 17, 2023
- SHA
- 375d0531
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. -->
Telugu-sentiment_analysis_summaries
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0009
- Accuracy: 0.5381
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0103 | 1.0 | 1758 | 1.0057 | 0.5381 |
| 1.0071 | 2.0 | 3516 | 1.0078 | 0.5381 |
| 1.0059 | 3.0 | 5274 | 1.0034 | 0.5381 |
| 1.0062 | 4.0 | 7032 | 1.0020 | 0.5381 |
| 1.005 | 5.0 | 8790 | 1.0017 | 0.5381 |
| 1.0043 | 6.0 | 10548 | 1.0015 | 0.5381 |
| 1.0042 | 7.0 | 12306 | 1.0014 | 0.5381 |
| 1.0039 | 8.0 | 14064 | 1.0011 | 0.5381 |
| 1.0027 | 9.0 | 15822 | 1.0010 | 0.5381 |
| 1.0021 | 10.0 | 17580 | 1.0009 | 0.5381 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- License
- mit
- Created
- Nov 17, 2023
- Updated
- Nov 17, 2023