
# 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|340.1608857823303|68.94318291614763|0.8756704046806436|0.8752436647173489|0.8760975609756098|0.8458536585365853|
|2|148.33983786634053|36.02450433204649|0.9217221135029354|0.9244357212953876|0.9190243902439025|0.8741463414634146|
|3|60.1067302722804|29.687325364822755|0.9230769230769231|0.9393939393939394|0.9073170731707317|0.8848780487804878|



{}
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 
