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hing-roberta-finetuned-TRAC-DS
This model is a fine-tuned version of l3cube-pune/hing-roberta on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1610
- Accuracy: 0.7149
- Precision: 0.6921
- Recall: 0.6946
- F1: 0.6932
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 |
|---|---|---|---|---|---|---|---|
| 0.7229 | 2.0 | 1224 | 0.7178 | 0.6928 | 0.6815 | 0.6990 | 0.6780 |
| 0.3258 | 3.99 | 2448 | 1.1610 | 0.7149 | 0.6921 | 0.6946 | 0.6932 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1
