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# irony_trained_final

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4770
- F1: 0.6879

## 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: 4.842398023893579e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.6852        | 1.0   | 716  | 0.6488          | 0.6530 |
| 0.6263        | 2.0   | 1432 | 0.7647          | 0.6511 |
| 0.4511        | 3.0   | 2148 | 1.2251          | 0.6764 |
| 0.2578        | 4.0   | 2864 | 1.4770          | 0.6879 |


### Framework versions

- Transformers 4.12.5
- Pytorch 1.9.1
- Datasets 1.16.1
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["tweet_eval"], "metrics": ["f1"], "model-index": [{"name": "irony_trained_final", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "tweet_eval", "type": "tweet_eval", "args": "irony"}, "metrics": [{"type": "f1", "value": 0.6879413493337545, "name": "F1"}]}]}]}
transformers pytorch distilbert text-classification generated_from_trainer dataset:tweet_eval license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-tweet_eval #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

irony\_trained\_final
=====================


This model is a fine-tuned version of distilbert-base-uncased on the tweet\_eval dataset.
It achieves the following results on the evaluation set:


* Loss: 1.4770
* F1: 0.6879


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: 4.842398023893579e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 0
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4


### Training results



### Framework versions


* Transformers 4.12.5
* Pytorch 1.9.1
* Datasets 1.16.1
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 4.842398023893579e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 0
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.12.5
* Pytorch 1.9.1
* Datasets 1.16.1
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-tweet_eval #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 4.842398023893579e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 0
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.12.5
* Pytorch 1.9.1
* Datasets 1.16.1
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #distilbert #text-classification #generated_from_trainer #dataset-tweet_eval #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 4.842398023893579e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 0
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 4### Training results### Framework versions


* Transformers 4.12.5
* Pytorch 1.9.1
* Datasets 1.16.1
* Tokenizers 0.10.3