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---
license: cc-by-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: l3cube-pune/hing-roberta
model-index:
- name: hing-roberta-CM-run-5
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-CM-run-5
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: 2.6447
- Accuracy: 0.7525
- Precision: 0.7030
- Recall: 0.7120
- F1: 0.7064
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.9492 | 1.0 | 497 | 0.7476 | 0.6157 | 0.6060 | 0.6070 | 0.5171 |
| 0.7013 | 2.0 | 994 | 0.7093 | 0.6982 | 0.6716 | 0.6864 | 0.6663 |
| 0.4871 | 3.0 | 1491 | 0.8294 | 0.7284 | 0.6714 | 0.6867 | 0.6723 |
| 0.3838 | 4.0 | 1988 | 1.1275 | 0.7505 | 0.6969 | 0.7025 | 0.6994 |
| 0.254 | 5.0 | 2485 | 1.3831 | 0.7264 | 0.6781 | 0.6975 | 0.6850 |
| 0.1765 | 6.0 | 2982 | 2.0625 | 0.7384 | 0.7068 | 0.6948 | 0.6896 |
| 0.1127 | 7.0 | 3479 | 1.9691 | 0.7425 | 0.6925 | 0.7065 | 0.6982 |
| 0.0757 | 8.0 | 3976 | 2.3871 | 0.7425 | 0.7183 | 0.6926 | 0.6924 |
| 0.0572 | 9.0 | 4473 | 2.4037 | 0.7344 | 0.6916 | 0.6929 | 0.6882 |
| 0.0458 | 10.0 | 4970 | 2.3062 | 0.7586 | 0.7174 | 0.7219 | 0.7164 |
| 0.0405 | 11.0 | 5467 | 2.5591 | 0.7445 | 0.6925 | 0.6964 | 0.6942 |
| 0.0292 | 12.0 | 5964 | 2.5215 | 0.7384 | 0.6875 | 0.6998 | 0.6917 |
| 0.0264 | 13.0 | 6461 | 2.7551 | 0.7586 | 0.7122 | 0.7035 | 0.7037 |
| 0.0299 | 14.0 | 6958 | 2.6536 | 0.7465 | 0.7114 | 0.7088 | 0.7035 |
| 0.0208 | 15.0 | 7455 | 2.5190 | 0.7505 | 0.6989 | 0.7083 | 0.7030 |
| 0.0263 | 16.0 | 7952 | 2.7092 | 0.7485 | 0.7076 | 0.6998 | 0.6962 |
| 0.0077 | 17.0 | 8449 | 2.5933 | 0.7525 | 0.7042 | 0.7143 | 0.7081 |
| 0.009 | 18.0 | 8946 | 2.5831 | 0.7485 | 0.6991 | 0.7152 | 0.7050 |
| 0.0108 | 19.0 | 9443 | 2.6360 | 0.7545 | 0.7050 | 0.7167 | 0.7098 |
| 0.0077 | 20.0 | 9940 | 2.6447 | 0.7525 | 0.7030 | 0.7120 | 0.7064 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1
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