
# Pretrained checkpoint: facebook/bart-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
- prompt_format: sentence aspect - sentiment

# Training results

|Epoch | Train loss| Subtask 3 f1 | Subtask 3 precision | Subtask 3 recall | Subtask4 accuracy |
|:----:|:---------:|:------------:|:-------------------:|:----------------:|:-----------------:|
|1|320.1579748761724|0.90401218892839|0.9427966101694916|0.8682926829268293|0.8575609756097561|
|2|143.87716180080315|0.9102822580645161|0.9416058394160584|0.8809756097560976|0.8721951219512195|
|3|55.62059011901874|0.9185989146521955|0.9291417165668663|0.9082926829268293|0.8878048780487805|



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

Pretrained checkpoint: facebook/bart-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
* prompt\_format: sentence aspect - sentiment


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




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