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---
license: apache-2.0
base_model: salohnana2018/HARD_without_dp_4248_camel_prepocessed_ASC
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ABSA-SentencePair-DAPT-HARD-4248-bert-base-Camel-MSA-ru2
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-HARD-4248-bert-base-Camel-MSA-ru2
This model is a fine-tuned version of [salohnana2018/HARD_without_dp_4248_camel_prepocessed_ASC](https://huggingface.co./salohnana2018/HARD_without_dp_4248_camel_prepocessed_ASC) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4529
- Accuracy: 0.8956
- F1: 0.8956
- Precision: 0.8956
- Recall: 0.8956
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4175 | 1.0 | 265 | 0.3482 | 0.8696 | 0.8696 | 0.8696 | 0.8696 |
| 0.2889 | 2.0 | 530 | 0.3280 | 0.8819 | 0.8819 | 0.8819 | 0.8819 |
| 0.1995 | 3.0 | 795 | 0.3343 | 0.8908 | 0.8908 | 0.8908 | 0.8908 |
| 0.1319 | 4.0 | 1060 | 0.3856 | 0.8932 | 0.8932 | 0.8932 | 0.8932 |
| 0.0855 | 5.0 | 1325 | 0.4529 | 0.8956 | 0.8956 | 0.8956 | 0.8956 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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