| | --- |
| | license: cc-by-4.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: hing-roberta-finetuned-code-mixed-DS |
| | results: [] |
| | --- |
| | |
| | <!-- 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](https://huggingface.co/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 |
| | |
