hing-mbert-finetuned-non-code-mixed-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: 1.7369
- Accuracy: 0.6667
- Precision: 0.6553
- Recall: 0.6428
- F1: 0.6459
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 |
---|---|---|---|---|---|---|---|
0.9413 | 1.0 | 926 | 0.8472 | 0.6354 | 0.6215 | 0.6247 | 0.6225 |
0.7278 | 2.0 | 1852 | 0.8966 | 0.6429 | 0.6408 | 0.6094 | 0.6122 |
0.4743 | 3.0 | 2778 | 1.2428 | 0.6613 | 0.6502 | 0.6420 | 0.6444 |
0.2558 | 4.0 | 3704 | 1.7369 | 0.6667 | 0.6553 | 0.6428 | 0.6459 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1
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