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# XLMR-ENIS-finetuned-stsb

This model is a fine-tuned version of [vesteinn/XLMR-ENIS](https://huggingface.co/vesteinn/XLMR-ENIS) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5232
- Pearson: 0.8915
- Spearmanr: 0.8888

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|
| No log        | 1.0   | 360  | 0.6330          | 0.8562  | 0.8570    |
| 1.2835        | 2.0   | 720  | 0.6368          | 0.8790  | 0.8781    |
| 0.4518        | 3.0   | 1080 | 0.5352          | 0.8883  | 0.8852    |
| 0.4518        | 4.0   | 1440 | 0.4881          | 0.8910  | 0.8885    |
| 0.288         | 5.0   | 1800 | 0.5232          | 0.8915  | 0.8888    |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.13.0
- Tokenizers 0.10.3

{"license": "agpl-3.0", "tags": ["generated_from_trainer"], "datasets": ["glue"], "metrics": ["spearmanr"], "pipeline_tag": "sentence-similarity", "base_model": "vesteinn/XLMR-ENIS", "model-index": [{"name": "XLMR-ENIS-finetuned-stsb", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "args": "stsb"}, "metrics": [{"type": "spearmanr", "value": 0.8887885342806044, "name": "Spearmanr"}]}]}]}
transformers pytorch tensorboard xlm-roberta text-classification generated_from_trainer sentence-similarity dataset:glue base_model:vesteinn/XLMR-ENIS license:agpl-3.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #text-classification #generated_from_trainer #sentence-similarity #dataset-glue #base_model-vesteinn/XLMR-ENIS #license-agpl-3.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

XLMR-ENIS-finetuned-stsb
========================


This model is a fine-tuned version of vesteinn/XLMR-ENIS on the glue dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5232
* Pearson: 0.8915
* Spearmanr: 0.8888


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: 5


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu111
* Datasets 1.13.0
* Tokenizers 0.10.3



### 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: 5 ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu111
* Datasets 1.13.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #xlm-roberta #text-classification #generated_from_trainer #sentence-similarity #dataset-glue #base_model-vesteinn/XLMR-ENIS #license-agpl-3.0 #model-index #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: 5 ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu111
* Datasets 1.13.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #xlm-roberta #text-classification #generated_from_trainer #sentence-similarity #dataset-glue #base_model-vesteinn/XLMR-ENIS #license-agpl-3.0 #model-index #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: 5### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.9.0+cu111
* Datasets 1.13.0
* Tokenizers 0.10.3