---
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-ru2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ABSA-SentencePair-DAPT-HARDARABS-bert-base-Camel-MSA-ru2

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: 1.7587
- Accuracy: 0.8941
- F1: 0.8941
- Precision: 0.8941
- Recall: 0.8941

## 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: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5254        | 1.0   | 265  | 0.4268          | 0.8483   | 0.8483 | 0.8483    | 0.8483 |
| 0.3572        | 2.0   | 530  | 0.3457          | 0.8563   | 0.8563 | 0.8563    | 0.8563 |
| 0.2477        | 3.0   | 795  | 0.5427          | 0.8795   | 0.8795 | 0.8795    | 0.8795 |
| 0.1905        | 4.0   | 1060 | 0.8314          | 0.8899   | 0.8899 | 0.8899    | 0.8899 |
| 0.1353        | 5.0   | 1325 | 1.0504          | 0.8852   | 0.8852 | 0.8852    | 0.8852 |
| 0.12          | 6.0   | 1590 | 0.7891          | 0.8842   | 0.8842 | 0.8842    | 0.8842 |
| 0.0749        | 7.0   | 1855 | 1.3696          | 0.8894   | 0.8894 | 0.8894    | 0.8894 |
| 0.097         | 8.0   | 2120 | 0.9817          | 0.8904   | 0.8904 | 0.8904    | 0.8904 |
| 0.0624        | 9.0   | 2385 | 1.0450          | 0.8847   | 0.8847 | 0.8847    | 0.8847 |
| 0.0582        | 10.0  | 2650 | 1.3148          | 0.8970   | 0.8970 | 0.8970    | 0.8970 |
| 0.0599        | 11.0  | 2915 | 1.4069          | 0.8946   | 0.8946 | 0.8946    | 0.8946 |
| 0.0451        | 12.0  | 3180 | 1.0183          | 0.8889   | 0.8889 | 0.8889    | 0.8889 |
| 0.0309        | 13.0  | 3445 | 1.3034          | 0.8932   | 0.8932 | 0.8932    | 0.8932 |
| 0.0251        | 14.0  | 3710 | 1.5148          | 0.8946   | 0.8946 | 0.8946    | 0.8946 |
| 0.0245        | 15.0  | 3975 | 1.5136          | 0.8946   | 0.8946 | 0.8946    | 0.8946 |
| 0.0153        | 16.0  | 4240 | 1.3876          | 0.8927   | 0.8927 | 0.8927    | 0.8927 |
| 0.0161        | 17.0  | 4505 | 1.6176          | 0.8885   | 0.8885 | 0.8885    | 0.8885 |
| 0.0166        | 18.0  | 4770 | 1.6110          | 0.8937   | 0.8937 | 0.8937    | 0.8937 |
| 0.0137        | 19.0  | 5035 | 1.7113          | 0.8960   | 0.8960 | 0.8960    | 0.8960 |
| 0.0111        | 20.0  | 5300 | 1.7241          | 0.8946   | 0.8946 | 0.8946    | 0.8946 |
| 0.0101        | 21.0  | 5565 | 1.6722          | 0.8970   | 0.8970 | 0.8970    | 0.8970 |
| 0.0142        | 22.0  | 5830 | 1.6423          | 0.8904   | 0.8904 | 0.8904    | 0.8904 |
| 0.0118        | 23.0  | 6095 | 1.6384          | 0.8904   | 0.8904 | 0.8904    | 0.8904 |
| 0.0083        | 24.0  | 6360 | 1.6616          | 0.8922   | 0.8922 | 0.8922    | 0.8922 |
| 0.0124        | 25.0  | 6625 | 1.9046          | 0.8951   | 0.8951 | 0.8951    | 0.8951 |
| 0.0154        | 26.0  | 6890 | 1.6547          | 0.8974   | 0.8974 | 0.8974    | 0.8974 |
| 0.0086        | 27.0  | 7155 | 1.6440          | 0.8932   | 0.8932 | 0.8932    | 0.8932 |
| 0.0077        | 28.0  | 7420 | 1.7566          | 0.8941   | 0.8941 | 0.8941    | 0.8941 |
| 0.0076        | 29.0  | 7685 | 1.7419          | 0.8937   | 0.8937 | 0.8937    | 0.8937 |
| 0.0078        | 30.0  | 7950 | 1.7587          | 0.8941   | 0.8941 | 0.8941    | 0.8941 |


### Framework versions

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