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xlm-roberta-base-lora-text-classification
sidd272/xlm-roberta-base-lora-text-classification
xlm-roberta-base-lora-text-classification is a machine learning model from sidd272. 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 Sep 25, 2023
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At a glance
- License
- mit
- Access
- Public
- Created
- Sep 25, 2023
- Updated
- Sep 25, 2023
- SHA
- 3477d5a4
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. -->
xlm-roberta-base-lora-text-classification
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5536
- Accuracy: {'accuracy': 0.8980555555555556}
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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|
| 0.4165 | 1.0 | 3600 | 0.4468 | {'accuracy': 0.895} |
| 0.5475 | 2.0 | 7200 | 0.4904 | {'accuracy': 0.8897222222222222} |
| 0.5878 | 3.0 | 10800 | 0.4564 | {'accuracy': 0.8986111111111111} |
| 0.6508 | 4.0 | 14400 | 0.4560 | {'accuracy': 0.8916666666666667} |
| 0.5914 | 5.0 | 18000 | 0.5437 | {'accuracy': 0.8883333333333333} |
| 0.5927 | 6.0 | 21600 | 0.5986 | {'accuracy': 0.8841666666666667} |
| 0.6044 | 7.0 | 25200 | 0.6523 | {'accuracy': 0.8791666666666667} |
| 0.6249 | 8.0 | 28800 | 0.6199 | {'accuracy': 0.8833333333333333} |
| 0.5427 | 9.0 | 32400 | 0.5363 | {'accuracy': 0.8969444444444444} |
| 0.5724 | 10.0 | 36000 | 0.5536 | {'accuracy': 0.8980555555555556} |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- License
- mit
- Created
- Sep 25, 2023
- Updated
- Sep 25, 2023