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# disaster-tweet-distilbert-1

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: 0.5571

## 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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- num_warmup_steps: 20%

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2888        | 0.12  | 12   | 2.3097          |
| 2.122         | 0.25  | 24   | 2.2960          |
| 2.2792        | 0.38  | 36   | 2.2720          |
| 2.3256        | 0.5   | 48   | 2.2368          |
| 2.2339        | 0.62  | 60   | 2.1904          |
| 2.2148        | 0.75  | 72   | 2.1360          |
| 2.0433        | 0.88  | 84   | 2.0723          |
| 2.0242        | 1.0   | 96   | 2.0028          |
| 1.8316        | 1.12  | 108  | 1.9302          |
| 1.9608        | 1.25  | 120  | 1.8508          |
| 1.8278        | 1.38  | 132  | 1.7635          |
| 1.7828        | 1.5   | 144  | 1.6711          |
| 1.5522        | 1.62  | 156  | 1.5747          |
| 1.474         | 1.75  | 168  | 1.4774          |
| 1.4762        | 1.88  | 180  | 1.3790          |
| 1.3439        | 2.0   | 192  | 1.2820          |
| 1.1465        | 2.12  | 204  | 1.1896          |
| 1.1755        | 2.25  | 216  | 1.1024          |
| 1.0085        | 2.38  | 228  | 1.0212          |
| 1.0492        | 2.5   | 240  | 0.9492          |
| 0.8642        | 2.62  | 252  | 0.8858          |
| 0.8554        | 2.75  | 264  | 0.8291          |
| 0.8534        | 2.88  | 276  | 0.7792          |
| 0.7013        | 3.0   | 288  | 0.7364          |
| 0.6414        | 3.12  | 300  | 0.7023          |
| 0.681         | 3.25  | 312  | 0.6707          |
| 0.6045        | 3.38  | 324  | 0.6441          |
| 0.6374        | 3.5   | 336  | 0.6193          |
| 0.6192        | 3.62  | 348  | 0.5988          |
| 0.5478        | 3.75  | 360  | 0.5831          |
| 0.5891        | 3.88  | 372  | 0.5693          |
| 0.5411        | 4.0   | 384  | 0.5571          |


### 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-1", "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-1
===========================


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: 0.5571


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: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4
* num\_warmup\_steps: 20%


### 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: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4
* num\_warmup\_steps: 20% ### 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: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4
* num\_warmup\_steps: 20% ### 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: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4
* num\_warmup\_steps: 20%### Training results### Framework versions


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