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# sentiment-analysis-twitter

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 new_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4579
- Accuracy: 0.7965

## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5315        | 1.0   | 157  | 0.4517          | 0.788    |
| 0.388         | 2.0   | 314  | 0.4416          | 0.8      |
| 0.3307        | 3.0   | 471  | 0.4579          | 0.7965   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu102
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["new_dataset"], "metrics": ["accuracy"], "model-index": [{"name": "sentiment-analysis-twitter", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "new_dataset", "type": "new_dataset", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7965, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard distilbert text-classification generated_from_trainer dataset:new_dataset license:apache-2.0 model-index autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-new_dataset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 

sentiment-analysis-twitter
==========================


This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the new\_dataset dataset.
It achieves the following results on the evaluation set:


* Loss: 0.4579
* Accuracy: 0.7965


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: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu102
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu102
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-new_dataset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu102
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #dataset-new_dataset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #has_space #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu102
* Datasets 2.1.0
* Tokenizers 0.12.1