<!-- 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. -->
hing-roberta-finetuned-code-mixed-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: 0.8512
- Accuracy: 0.7706
- Precision: 0.7217
- Recall: 0.7233
- F1: 0.7222
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: 4.932923543227153e-05
- train_batch_size: 8
- eval_batch_size: 16
- 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: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
1.0216 | 1.0 | 497 | 1.1363 | 0.5392 | 0.4228 | 0.3512 | 0.2876 |
0.9085 | 2.0 | 994 | 0.7599 | 0.6761 | 0.6247 | 0.6294 | 0.5902 |
0.676 | 3.0 | 1491 | 0.7415 | 0.7505 | 0.6946 | 0.7034 | 0.6983 |
0.4404 | 4.0 | 1988 | 0.8512 | 0.7706 | 0.7217 | 0.7233 | 0.7222 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1