
# Pretrained checkpoint: roberta-large-mnli
# Traning hyperparameters:
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 24
- eval_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

# Training results

|Epoch | Train loss| Test loss | Subtask 3 f1 | Subtask 3 precision | Subtask 3 recall | Subtask4 accuracy |
|:----:|:---------:|:---------:|:------------:|:-------------------:|:----------------:|:-----------------:|
|1|342.2936071057338|57.76338505232707|0.9101978691019786|0.9482029598308668|0.8751219512195122|0.8517073170731707|
|2|158.99010239201016|40.69869995024055|0.9054122407688416|0.9401260504201681|0.8731707317073171|0.8780487804878049|
|3|68.2056962888746|32.117333286470966|0.9244444444444445|0.936|0.9131707317073171|0.8887804878048781|



{}
transformers pytorch roberta text-classification autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #autotrain_compatible #endpoints_compatible #region-us 

Pretrained checkpoint: roberta-large-mnli
=========================================


Traning hyperparameters:
========================


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 24
* eval\_batch\_size: 24
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3


Training results
================




TAGS
#transformers #pytorch #roberta #text-classification #autotrain_compatible #endpoints_compatible #region-us 
