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hing-mbert-finetuned-combined-DS
This model is a fine-tuned version of l3cube-pune/hing-mbert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4833
- Accuracy: 0.6721
- Precision: 0.6460
- Recall: 0.6443
- F1: 0.6447
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: 4.8796394086479776e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 43
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.7382 | 2.0 | 1423 | 0.8027 | 0.6749 | 0.6544 | 0.6590 | 0.6538 |
| 0.2943 | 4.0 | 2846 | 1.4833 | 0.6721 | 0.6460 | 0.6443 | 0.6447 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1
