
# distilroberta-current

This model classifies articles as current (covering or discussing current events) or not current (not relating to current events).

The model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on a dataset of articles labeled using weak-supervision and manual labeling

It achieves the following results on the evaluation set:
- Loss: 0.1745
- Acc: 0.9355

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 12345
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 16
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Acc    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 11   | 0.6559          | 0.7097 |
| 0.6762        | 2.0   | 22   | 0.5627          | 0.7097 |
| 0.5432        | 3.0   | 33   | 0.4606          | 0.7097 |
| 0.5432        | 4.0   | 44   | 0.3651          | 0.8065 |
| 0.411         | 5.0   | 55   | 0.2512          | 0.9194 |
| 0.269         | 6.0   | 66   | 0.2774          | 0.9355 |
| 0.269         | 7.0   | 77   | 0.2062          | 0.8710 |
| 0.2294        | 8.0   | 88   | 0.2598          | 0.9355 |
| 0.1761        | 9.0   | 99   | 0.1745          | 0.9355 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.1
- Datasets 1.17.0
- Tokenizers 0.10.3

{"license": "other", "tags": ["generated_from_trainer"], "model-index": [{"name": "distilroberta-current", "results": []}]}
transformers pytorch roberta text-classification generated_from_trainer license:other autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-other #autotrain_compatible #endpoints_compatible #region-us 

distilroberta-current
=====================


This model classifies articles as current (covering or discussing current events) or not current (not relating to current events).


The model is a fine-tuned version of distilroberta-base on a dataset of articles labeled using weak-supervision and manual labeling


It achieves the following results on the evaluation set:


* Loss: 0.1745
* Acc: 0.9355


Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 12345
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 16
* num\_epochs: 20
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.1
* Datasets 1.17.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 12345
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 16
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.1
* Datasets 1.17.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-other #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 12345
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 16
* num\_epochs: 20
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.1
* Datasets 1.17.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-other #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 12345
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 16
* num\_epochs: 20
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.10.1
* Datasets 1.17.0
* Tokenizers 0.10.3