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# finetuned_token_itr0_2e-05_all_16_02_2022-21_08_55

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: 0.2853
- Precision: 0.1677
- Recall: 0.3106
- F1: 0.2178
- Accuracy: 0.8755

## 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: 32
- eval_batch_size: 32
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 30   | 0.3452          | 0.0526    | 0.1055 | 0.0702 | 0.8507   |
| No log        | 2.0   | 60   | 0.2598          | 0.1575    | 0.2680 | 0.1984 | 0.8909   |
| No log        | 3.0   | 90   | 0.2398          | 0.1866    | 0.2982 | 0.2295 | 0.9007   |
| No log        | 4.0   | 120  | 0.2354          | 0.1949    | 0.3049 | 0.2378 | 0.9002   |
| No log        | 5.0   | 150  | 0.2314          | 0.2026    | 0.3166 | 0.2471 | 0.9004   |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "finetuned_token_itr0_2e-05_all_16_02_2022-21_08_55", "results": []}]}
transformers pytorch tensorboard distilbert token-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

finetuned\_token\_itr0\_2e-05\_all\_16\_02\_2022-21\_08\_55
===========================================================


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: 0.2853
* Precision: 0.1677
* Recall: 0.3106
* F1: 0.2178
* Accuracy: 0.8755


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: 32
* eval\_batch\_size: 32
* 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 4.15.0
* Pytorch 1.10.1+cu113
* Datasets 1.18.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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 4.15.0
* Pytorch 1.10.1+cu113
* Datasets 1.18.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #distilbert #token-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: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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 4.15.0
* Pytorch 1.10.1+cu113
* Datasets 1.18.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #distilbert #token-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: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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 4.15.0
* Pytorch 1.10.1+cu113
* Datasets 1.18.0
* Tokenizers 0.10.3