
<!-- 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. -->

# disaster-tweet-1

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: 0.4642

## 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: 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.714         | 0.12  | 12   | 0.7096          |
| 0.7103        | 0.25  | 24   | 0.7075          |
| 0.7078        | 0.38  | 36   | 0.7041          |
| 0.7029        | 0.5   | 48   | 0.6999          |
| 0.7063        | 0.62  | 60   | 0.6944          |
| 0.6955        | 0.75  | 72   | 0.6879          |
| 0.6894        | 0.88  | 84   | 0.6806          |
| 0.6799        | 1.0   | 96   | 0.6723          |
| 0.6722        | 1.12  | 108  | 0.6634          |
| 0.6677        | 1.25  | 120  | 0.6533          |
| 0.6611        | 1.38  | 132  | 0.6439          |
| 0.6392        | 1.5   | 144  | 0.6326          |
| 0.6344        | 1.62  | 156  | 0.6203          |
| 0.6189        | 1.75  | 168  | 0.6057          |
| 0.6121        | 1.88  | 180  | 0.5900          |
| 0.5717        | 2.0   | 192  | 0.5729          |
| 0.5578        | 2.12  | 204  | 0.5563          |
| 0.5556        | 2.25  | 216  | 0.5400          |
| 0.5433        | 2.38  | 228  | 0.5241          |
| 0.5058        | 2.5   | 240  | 0.5086          |
| 0.5047        | 2.62  | 252  | 0.4948          |
| 0.4783        | 2.75  | 264  | 0.4825          |
| 0.4931        | 2.88  | 276  | 0.4724          |
| 0.4364        | 3.0   | 288  | 0.4642          |


### Framework versions

- Transformers 4.28.0
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "model-index": [{"name": "disaster-tweet-1", "results": []}]}
transformers pytorch tensorboard roberta text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

disaster-tweet-1
================


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: 0.4642


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: 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: 3


### Training results



### Framework versions


* Transformers 4.28.0
* 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: 3 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #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: 3 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2