
# Pretrained checkpoint: microsoft/deberta-large
# Traning hyperparameters:
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- prompt_format: sentence aspect - sentiment

# Training results

|Epoch | Train loss| Subtask 3 f1 | Subtask 3 precision | Subtask 3 recall | Subtask4 accuracy |
|:----:|:---------:|:------------:|:-------------------:|:----------------:|:-----------------:|
|1|355.13336368463933|0.8388829215896885|0.9330943847072879|0.7619512195121951|0.8360975609756097|
|2|171.31726237665862|0.9082615306639635|0.9451476793248945|0.8741463414634146|0.8809756097560976|
|3|96.62600621895399|0.9191321499013807|0.9292123629112662|0.9092682926829269|0.8985365853658537|
|4|46.02018972591031|0.920743639921722|0.9234543670264965|0.9180487804878049|0.8848780487804878|
|5|18.8767371326976|0.9239130434782609|0.9359359359359359|0.9121951219512195|0.9014634146341464|



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

Pretrained checkpoint: microsoft/deberta-large
==============================================


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


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5
* prompt\_format: sentence aspect - sentiment


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




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