---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
base_model: salohnana2018/CAMEL-BERT-MSA-domianAdaption-Single-ABSA-HARD
model-index:
- name: ABSA-SentencePair-DAPT-HARDARABS-bert-base-Camel-MSA-ru1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# ABSA-SentencePair-DAPT-HARDARABS-bert-base-Camel-MSA-ru1

This model is a fine-tuned version of [salohnana2018/CAMEL-BERT-MSA-domianAdaption-Single-ABSA-HARD](https://huggingface.co./salohnana2018/CAMEL-BERT-MSA-domianAdaption-Single-ABSA-HARD) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6590
- Accuracy: 0.8965
- F1: 0.8965
- Precision: 0.8965
- Recall: 0.8965

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 25
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5505        | 1.0   | 265  | 0.4846          | 0.7703   | 0.7703 | 0.7703    | 0.7703 |
| 0.354         | 2.0   | 530  | 0.3727          | 0.8852   | 0.8852 | 0.8852    | 0.8852 |
| 0.2455        | 3.0   | 795  | 0.4606          | 0.8582   | 0.8582 | 0.8582    | 0.8582 |
| 0.179         | 4.0   | 1060 | 0.5599          | 0.8771   | 0.8771 | 0.8771    | 0.8771 |
| 0.1452        | 5.0   | 1325 | 0.8984          | 0.8795   | 0.8795 | 0.8795    | 0.8795 |
| 0.1076        | 6.0   | 1590 | 0.8935          | 0.8960   | 0.8960 | 0.8960    | 0.8960 |
| 0.093         | 7.0   | 1855 | 0.6251          | 0.8757   | 0.8757 | 0.8757    | 0.8757 |
| 0.0779        | 8.0   | 2120 | 0.9415          | 0.8899   | 0.8899 | 0.8899    | 0.8899 |
| 0.0653        | 9.0   | 2385 | 0.9360          | 0.8965   | 0.8965 | 0.8965    | 0.8965 |
| 0.0514        | 10.0  | 2650 | 1.0234          | 0.8889   | 0.8889 | 0.8889    | 0.8889 |
| 0.0367        | 11.0  | 2915 | 1.3198          | 0.8951   | 0.8951 | 0.8951    | 0.8951 |
| 0.0414        | 12.0  | 3180 | 1.1830          | 0.8833   | 0.8833 | 0.8833    | 0.8833 |
| 0.0396        | 13.0  | 3445 | 1.1262          | 0.8885   | 0.8885 | 0.8885    | 0.8885 |
| 0.0338        | 14.0  | 3710 | 1.3073          | 0.8970   | 0.8970 | 0.8970    | 0.8970 |
| 0.0204        | 15.0  | 3975 | 1.2894          | 0.8946   | 0.8946 | 0.8946    | 0.8946 |
| 0.0232        | 16.0  | 4240 | 1.3265          | 0.8960   | 0.8960 | 0.8960    | 0.8960 |
| 0.0203        | 17.0  | 4505 | 1.2467          | 0.8974   | 0.8974 | 0.8974    | 0.8974 |
| 0.012         | 18.0  | 4770 | 1.5870          | 0.8960   | 0.8960 | 0.8960    | 0.8960 |
| 0.0155        | 19.0  | 5035 | 1.5296          | 0.8974   | 0.8974 | 0.8974    | 0.8974 |
| 0.0112        | 20.0  | 5300 | 1.6052          | 0.9026   | 0.9026 | 0.9026    | 0.9026 |
| 0.0109        | 21.0  | 5565 | 1.5280          | 0.8974   | 0.8974 | 0.8974    | 0.8974 |
| 0.012         | 22.0  | 5830 | 1.5513          | 0.8941   | 0.8941 | 0.8941    | 0.8941 |
| 0.0103        | 23.0  | 6095 | 1.6142          | 0.8984   | 0.8984 | 0.8984    | 0.8984 |
| 0.0116        | 24.0  | 6360 | 1.5363          | 0.8965   | 0.8965 | 0.8965    | 0.8965 |
| 0.0104        | 25.0  | 6625 | 1.6729          | 0.8984   | 0.8984 | 0.8984    | 0.8984 |
| 0.0079        | 26.0  | 6890 | 1.7198          | 0.8993   | 0.8993 | 0.8993    | 0.8993 |
| 0.0093        | 27.0  | 7155 | 1.5210          | 0.8941   | 0.8941 | 0.8941    | 0.8941 |
| 0.0077        | 28.0  | 7420 | 1.6023          | 0.8960   | 0.8960 | 0.8960    | 0.8960 |
| 0.0077        | 29.0  | 7685 | 1.6430          | 0.8960   | 0.8960 | 0.8960    | 0.8960 |
| 0.0073        | 30.0  | 7950 | 1.6590          | 0.8965   | 0.8965 | 0.8965    | 0.8965 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2