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# hing-roberta-CM-run-4

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: 2.5827
- Accuracy: 0.7525
- Precision: 0.6967
- Recall: 0.7004
- F1: 0.6980

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.8734        | 1.0   | 497  | 0.7673          | 0.7203   | 0.6617    | 0.6600 | 0.6604 |
| 0.6245        | 2.0   | 994  | 0.7004          | 0.7485   | 0.6951    | 0.7137 | 0.7015 |
| 0.4329        | 3.0   | 1491 | 1.0469          | 0.7223   | 0.6595    | 0.6640 | 0.6538 |
| 0.2874        | 4.0   | 1988 | 1.3103          | 0.7586   | 0.7064    | 0.7157 | 0.7104 |
| 0.1837        | 5.0   | 2485 | 1.7916          | 0.7425   | 0.6846    | 0.6880 | 0.6861 |
| 0.1121        | 6.0   | 2982 | 2.0721          | 0.7465   | 0.7064    | 0.7041 | 0.7003 |
| 0.0785        | 7.0   | 3479 | 2.3469          | 0.7425   | 0.6898    | 0.6795 | 0.6807 |
| 0.0609        | 8.0   | 3976 | 2.2775          | 0.7404   | 0.6819    | 0.6881 | 0.6845 |
| 0.0817        | 9.0   | 4473 | 2.1992          | 0.7686   | 0.7342    | 0.7147 | 0.7166 |
| 0.042         | 10.0  | 4970 | 2.2359          | 0.7565   | 0.7211    | 0.7141 | 0.7106 |
| 0.0463        | 11.0  | 5467 | 2.2291          | 0.7646   | 0.7189    | 0.7186 | 0.7177 |
| 0.027         | 12.0  | 5964 | 2.3955          | 0.7525   | 0.6994    | 0.7073 | 0.7028 |
| 0.0314        | 13.0  | 6461 | 2.4256          | 0.7565   | 0.7033    | 0.7153 | 0.7082 |
| 0.0251        | 14.0  | 6958 | 2.4578          | 0.7565   | 0.7038    | 0.7025 | 0.7027 |
| 0.0186        | 15.0  | 7455 | 2.5984          | 0.7565   | 0.7141    | 0.6945 | 0.6954 |
| 0.0107        | 16.0  | 7952 | 2.5068          | 0.7425   | 0.6859    | 0.7016 | 0.6912 |
| 0.0134        | 17.0  | 8449 | 2.5876          | 0.7606   | 0.7018    | 0.7041 | 0.7029 |
| 0.0145        | 18.0  | 8946 | 2.6011          | 0.7626   | 0.7072    | 0.7079 | 0.7073 |
| 0.0108        | 19.0  | 9443 | 2.5861          | 0.7545   | 0.6973    | 0.7017 | 0.6990 |
| 0.0076        | 20.0  | 9940 | 2.5827          | 0.7525   | 0.6967    | 0.7004 | 0.6980 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.10.1+cu111
- Datasets 2.3.2
- Tokenizers 0.12.1

{"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-4", "results": []}]}
transformers pytorch xlm-roberta text-classification generated_from_trainer base_model:l3cube-pune/hing-roberta license:cc-by-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #base_model-l3cube-pune/hing-roberta #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 

hing-roberta-CM-run-4
=====================


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: 2.5827
* Accuracy: 0.7525
* Precision: 0.6967
* Recall: 0.7004
* F1: 0.6980


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



### Framework versions


* Transformers 4.20.1
* Pytorch 1.10.1+cu111
* Datasets 2.3.2
* Tokenizers 0.12.1



### 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 ### Framework versions


* Transformers 4.20.1
* Pytorch 1.10.1+cu111
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #base_model-l3cube-pune/hing-roberta #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### 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 ### Framework versions


* Transformers 4.20.1
* Pytorch 1.10.1+cu111
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #xlm-roberta #text-classification #generated_from_trainer #base_model-l3cube-pune/hing-roberta #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 
### 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### Framework versions


* Transformers 4.20.1
* Pytorch 1.10.1+cu111
* Datasets 2.3.2
* Tokenizers 0.12.1