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# disaster-tweet-distilbert

This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4605

## 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: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 7
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- num_warmup_steps: 10%

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2877        | 0.12  | 12   | 2.3051          |
| 2.1129        | 0.25  | 24   | 2.2778          |
| 2.2514        | 0.38  | 36   | 2.2299          |
| 2.2691        | 0.5   | 48   | 2.1606          |
| 2.1401        | 0.62  | 60   | 2.0706          |
| 2.075         | 0.75  | 72   | 1.9672          |
| 1.8594        | 0.88  | 84   | 1.8498          |
| 1.7927        | 1.0   | 96   | 1.7257          |
| 1.5639        | 1.12  | 108  | 1.6010          |
| 1.6001        | 1.25  | 120  | 1.4670          |
| 1.4207        | 1.38  | 132  | 1.3314          |
| 1.3183        | 1.5   | 144  | 1.1993          |
| 1.0767        | 1.62  | 156  | 1.0798          |
| 0.9672        | 1.75  | 168  | 0.9742          |
| 0.9523        | 1.88  | 180  | 0.8821          |
| 0.813         | 2.0   | 192  | 0.8027          |
| 0.7004        | 2.12  | 204  | 0.7424          |
| 0.7044        | 2.25  | 216  | 0.6904          |
| 0.6218        | 2.38  | 228  | 0.6495          |
| 0.6472        | 2.5   | 240  | 0.6158          |
| 0.5585        | 2.62  | 252  | 0.5896          |
| 0.5613        | 2.75  | 264  | 0.5685          |
| 0.5911        | 2.88  | 276  | 0.5499          |
| 0.5062        | 3.0   | 288  | 0.5357          |
| 0.4806        | 3.12  | 300  | 0.5257          |
| 0.4862        | 3.25  | 312  | 0.5091          |
| 0.4433        | 3.38  | 324  | 0.4997          |
| 0.486         | 3.5   | 336  | 0.4892          |
| 0.4746        | 3.62  | 348  | 0.4802          |
| 0.4317        | 3.75  | 360  | 0.4759          |
| 0.4874        | 3.88  | 372  | 0.4670          |
| 0.4411        | 4.0   | 384  | 0.4605          |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "disaster-tweet-distilbert", "results": []}]}
transformers pytorch tensorboard distilbert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

disaster-tweet-distilbert
=========================


This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4605


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: 3e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 7
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4
* num\_warmup\_steps: 10%


### 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: 3e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 7
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4
* num\_warmup\_steps: 10% ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 7
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4
* num\_warmup\_steps: 10% ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.13.0
* Datasets 2.1.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-05
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 7
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4
* num\_warmup\_steps: 10%### Training results### Framework versions


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