metadata
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
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
| 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