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# raw_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: 0.4184


### 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7201        | 0.12  | 12   | 0.7164          |
| 0.7234        | 0.25  | 24   | 0.7148          |
| 0.7128        | 0.38  | 36   | 0.7121          |
| 0.7122        | 0.5   | 48   | 0.7086          |
| 0.7074        | 0.62  | 60   | 0.7042          |
| 0.699         | 0.75  | 72   | 0.6990          |
| 0.6989        | 0.88  | 84   | 0.6934          |
| 0.6904        | 1.0   | 96   | 0.6871          |
| 0.6884        | 1.12  | 108  | 0.6801          |
| 0.6793        | 1.25  | 120  | 0.6723          |
| 0.6746        | 1.38  | 132  | 0.6638          |
| 0.6635        | 1.5   | 144  | 0.6539          |
| 0.647         | 1.62  | 156  | 0.6426          |
| 0.6418        | 1.75  | 168  | 0.6293          |
| 0.6287        | 1.88  | 180  | 0.6140          |
| 0.5938        | 2.0   | 192  | 0.5959          |
| 0.5869        | 2.12  | 204  | 0.5768          |
| 0.5718        | 2.25  | 216  | 0.5586          |
| 0.5638        | 2.38  | 228  | 0.5413          |
| 0.5265        | 2.5   | 240  | 0.5259          |
| 0.5165        | 2.62  | 252  | 0.5111          |
| 0.4966        | 2.75  | 264  | 0.4987          |
| 0.5072        | 2.88  | 276  | 0.4886          |
| 0.456         | 3.0   | 288  | 0.4827          |
| 0.458         | 3.12  | 300  | 0.4704          |
| 0.434         | 3.25  | 312  | 0.4647          |
| 0.421         | 3.38  | 324  | 0.4604          |
| 0.4679        | 3.5   | 336  | 0.4546          |
| 0.4463        | 3.62  | 348  | 0.4498          |
| 0.4288        | 3.75  | 360  | 0.4500          |
| 0.4261        | 3.88  | 372  | 0.4406          |
| 0.4314        | 4.0   | 384  | 0.4420          |
| 0.3848        | 4.12  | 396  | 0.4349          |
| 0.4145        | 4.25  | 408  | 0.4354          |
| 0.4151        | 4.38  | 420  | 0.4277          |
| 0.4034        | 4.5   | 432  | 0.4273          |
| 0.3933        | 4.62  | 444  | 0.4295          |
| 0.4171        | 4.75  | 456  | 0.4216          |
| 0.3926        | 4.88  | 468  | 0.4179          |
| 0.3739        | 5.0   | 480  | 0.4184          |


### 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": "raw_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 

raw\_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: 0.4184


### 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