
<!-- 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. -->

# preprocessed_disaster_tweets

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4125


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6693        | 0.12  | 12   | 0.6626          |
| 0.6712        | 0.25  | 24   | 0.6614          |
| 0.6604        | 0.38  | 36   | 0.6595          |
| 0.6667        | 0.5   | 48   | 0.6571          |
| 0.6574        | 0.62  | 60   | 0.6540          |
| 0.6595        | 0.75  | 72   | 0.6500          |
| 0.6545        | 0.88  | 84   | 0.6456          |
| 0.6502        | 1.0   | 96   | 0.6405          |
| 0.6437        | 1.12  | 108  | 0.6347          |
| 0.6393        | 1.25  | 120  | 0.6280          |
| 0.6496        | 1.38  | 132  | 0.6218          |
| 0.6196        | 1.5   | 144  | 0.6146          |
| 0.6299        | 1.62  | 156  | 0.6068          |
| 0.6068        | 1.75  | 168  | 0.5976          |
| 0.6038        | 1.88  | 180  | 0.5878          |
| 0.5786        | 2.0   | 192  | 0.5770          |
| 0.5691        | 2.12  | 204  | 0.5663          |
| 0.5619        | 2.25  | 216  | 0.5552          |
| 0.5758        | 2.38  | 228  | 0.5442          |
| 0.5249        | 2.5   | 240  | 0.5326          |
| 0.5264        | 2.62  | 252  | 0.5207          |
| 0.5167        | 2.75  | 264  | 0.5090          |
| 0.5259        | 2.88  | 276  | 0.4991          |
| 0.4738        | 3.0   | 288  | 0.4917          |
| 0.4681        | 3.12  | 300  | 0.4795          |
| 0.4482        | 3.25  | 312  | 0.4698          |
| 0.4354        | 3.38  | 324  | 0.4616          |
| 0.465         | 3.5   | 336  | 0.4531          |
| 0.4593        | 3.62  | 348  | 0.4469          |
| 0.4294        | 3.75  | 360  | 0.4467          |
| 0.4284        | 3.88  | 372  | 0.4374          |
| 0.4337        | 4.0   | 384  | 0.4347          |
| 0.3805        | 4.12  | 396  | 0.4318          |
| 0.4113        | 4.25  | 408  | 0.4269          |
| 0.4155        | 4.38  | 420  | 0.4201          |
| 0.4112        | 4.5   | 432  | 0.4205          |
| 0.3921        | 4.62  | 444  | 0.4228          |
| 0.4018        | 4.75  | 456  | 0.4151          |
| 0.3995        | 4.88  | 468  | 0.4102          |
| 0.3891        | 5.0   | 480  | 0.4125          |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2

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

preprocessed\_disaster\_tweets
==============================


This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4125


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2