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# model

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unkown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9150
- Accuracy: 0.2662

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.0528        | 0.44  | 1000 | 3.0265          | 0.2223   |
| 2.9836        | 0.89  | 2000 | 2.9263          | 0.2332   |
| 2.7409        | 1.33  | 3000 | 2.9041          | 0.2533   |
| 2.7905        | 1.77  | 4000 | 2.8763          | 0.2606   |
| 2.4359        | 2.22  | 5000 | 2.9072          | 0.2642   |
| 2.4507        | 2.66  | 6000 | 2.9230          | 0.2644   |


### Framework versions

- Transformers 4.7.0.dev0
- Pytorch 1.8.1+cu102
- Datasets 1.8.0
- Tokenizers 0.10.3


{"license": "apache-2.0", "tags": ["generated-from-trainer"], "datasets": ["julien-c/reactiongif"], "metrics": ["accuracy"]}
transformers pytorch tensorboard safetensors roberta text-classification generated-from-trainer dataset:julien-c/reactiongif license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #text-classification #generated-from-trainer #dataset-julien-c/reactiongif #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

model
=====


This model is a fine-tuned version of distilroberta-base on an unkown dataset.
It achieves the following results on the evaluation set:


* Loss: 2.9150
* Accuracy: 0.2662


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: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* 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 4.7.0.dev0
* Pytorch 1.8.1+cu102
* Datasets 1.8.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* 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 4.7.0.dev0
* Pytorch 1.8.1+cu102
* Datasets 1.8.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #text-classification #generated-from-trainer #dataset-julien-c/reactiongif #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* 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 4.7.0.dev0
* Pytorch 1.8.1+cu102
* Datasets 1.8.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #text-classification #generated-from-trainer #dataset-julien-c/reactiongif #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* 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 4.7.0.dev0
* Pytorch 1.8.1+cu102
* Datasets 1.8.0
* Tokenizers 0.10.3