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# distilbert-base-uncased-finetuned-sarcasm

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3075
- Matthews Correlation: 0.4109

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| No log        | 1.0   | 57   | 0.7322          | 0.0                  |
| No log        | 2.0   | 114  | 0.6734          | 0.1752               |
| No log        | 3.0   | 171  | 0.6436          | 0.3228               |
| No log        | 4.0   | 228  | 0.7826          | 0.2778               |
| No log        | 5.0   | 285  | 1.0203          | 0.2707               |
| No log        | 6.0   | 342  | 1.0190          | 0.3356               |
| No log        | 7.0   | 399  | 1.1675          | 0.3177               |
| No log        | 8.0   | 456  | 1.5206          | 0.2514               |
| 0.3597        | 9.0   | 513  | 1.5789          | 0.4097               |
| 0.3597        | 10.0  | 570  | 1.5752          | 0.3740               |
| 0.3597        | 11.0  | 627  | 1.9003          | 0.3506               |
| 0.3597        | 12.0  | 684  | 1.9354          | 0.3855               |
| 0.3597        | 13.0  | 741  | 1.9770          | 0.3289               |
| 0.3597        | 14.0  | 798  | 1.9802          | 0.3583               |
| 0.3597        | 15.0  | 855  | 2.1322          | 0.3255               |
| 0.3597        | 16.0  | 912  | 2.1541          | 0.2994               |
| 0.3597        | 17.0  | 969  | 2.2047          | 0.2992               |
| 0.0329        | 18.0  | 1026 | 2.0794          | 0.3466               |
| 0.0329        | 19.0  | 1083 | 2.0705          | 0.3012               |
| 0.0329        | 20.0  | 1140 | 2.0158          | 0.3759               |
| 0.0329        | 21.0  | 1197 | 2.3999          | 0.3151               |
| 0.0329        | 22.0  | 1254 | 2.1017          | 0.3917               |
| 0.0329        | 23.0  | 1311 | 2.3275          | 0.3255               |
| 0.0329        | 24.0  | 1368 | 2.2258          | 0.3386               |
| 0.0329        | 25.0  | 1425 | 2.3628          | 0.3406               |
| 0.0329        | 26.0  | 1482 | 2.4197          | 0.3077               |
| 0.0145        | 27.0  | 1539 | 2.2661          | 0.3759               |
| 0.0145        | 28.0  | 1596 | 2.4074          | 0.3077               |
| 0.0145        | 29.0  | 1653 | 2.3326          | 0.3255               |
| 0.0145        | 30.0  | 1710 | 2.2813          | 0.3740               |
| 0.0145        | 31.0  | 1767 | 2.3242          | 0.3181               |
| 0.0145        | 32.0  | 1824 | 2.5039          | 0.2930               |
| 0.0145        | 33.0  | 1881 | 2.6045          | 0.3151               |
| 0.0145        | 34.0  | 1938 | 2.3075          | 0.4109               |
| 0.0145        | 35.0  | 1995 | 2.3572          | 0.3759               |
| 0.0129        | 36.0  | 2052 | 2.3833          | 0.3759               |
| 0.0129        | 37.0  | 2109 | 2.6260          | 0.3009               |
| 0.0129        | 38.0  | 2166 | 2.6132          | 0.3289               |
| 0.0129        | 39.0  | 2223 | 2.4151          | 0.3989               |
| 0.0129        | 40.0  | 2280 | 2.5695          | 0.3360               |
| 0.0129        | 41.0  | 2337 | 2.3902          | 0.3989               |
| 0.0129        | 42.0  | 2394 | 2.4388          | 0.3759               |
| 0.0129        | 43.0  | 2451 | 2.6323          | 0.3289               |
| 0.0065        | 44.0  | 2508 | 2.6131          | 0.3553               |
| 0.0065        | 45.0  | 2565 | 2.4426          | 0.3958               |
| 0.0065        | 46.0  | 2622 | 2.4481          | 0.3958               |
| 0.0065        | 47.0  | 2679 | 2.4440          | 0.3958               |
| 0.0065        | 48.0  | 2736 | 2.4689          | 0.3784               |
| 0.0065        | 49.0  | 2793 | 2.4725          | 0.3784               |
| 0.0065        | 50.0  | 2850 | 2.4718          | 0.3784               |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["matthews_correlation"], "model-index": [{"name": "distilbert-base-uncased-finetuned-sarcasm", "results": []}]}
transformers pytorch tensorboard safetensors distilbert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distilbert-base-uncased-finetuned-sarcasm
=========================================


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


* Loss: 2.3075
* Matthews Correlation: 0.4109


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: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #safetensors #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: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3