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# paper_feedback_intent

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3621
- Accuracy: 0.9302
- Precision: 0.9307
- Recall: 0.9302
- F1: 0.9297

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.9174        | 1.0   | 11   | 0.7054          | 0.7907   | 0.7903    | 0.7907 | 0.7861 |
| 0.6917        | 2.0   | 22   | 0.4665          | 0.8140   | 0.8134    | 0.8140 | 0.8118 |
| 0.4276        | 3.0   | 33   | 0.3326          | 0.9070   | 0.9065    | 0.9070 | 0.9041 |
| 0.2656        | 4.0   | 44   | 0.3286          | 0.9070   | 0.9065    | 0.9070 | 0.9041 |
| 0.1611        | 5.0   | 55   | 0.3044          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
| 0.1025        | 6.0   | 66   | 0.3227          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
| 0.0799        | 7.0   | 77   | 0.3216          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
| 0.0761        | 8.0   | 88   | 0.3529          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
| 0.0479        | 9.0   | 99   | 0.3605          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |
| 0.0358        | 10.0  | 110  | 0.3621          | 0.9302   | 0.9307    | 0.9302 | 0.9297 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall", "f1"], "model-index": [{"name": "paper_feedback_intent", "results": []}]}
transformers pytorch tensorboard roberta text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

paper\_feedback\_intent
=======================


This model is a fine-tuned version of roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3621
* Accuracy: 0.9302
* Precision: 0.9307
* Recall: 0.9302
* F1: 0.9297


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: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.17.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6