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---
base_model: AIRI-Institute/gena-lm-bert-base-t2t-multi
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: gut_1024-finetuned-lora-bert-base-t2t-multi
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. -->
# gut_1024-finetuned-lora-bert-base-t2t-multi
This model is a fine-tuned version of [AIRI-Institute/gena-lm-bert-base-t2t-multi](https://huggingface.co/AIRI-Institute/gena-lm-bert-base-t2t-multi) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4764
- F1: 0.8478
- Mcc Score: 0.5903
- Accuracy: 0.8049
## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Mcc Score | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:|
| 0.7012 | 0.02 | 100 | 0.6683 | 0.7478 | 0.0 | 0.5971 |
| 0.7003 | 0.04 | 200 | 0.6391 | 0.7825 | 0.3306 | 0.6710 |
| 0.6583 | 0.05 | 300 | 0.6211 | 0.7853 | 0.3430 | 0.6778 |
| 0.6381 | 0.07 | 400 | 0.6512 | 0.7812 | 0.3247 | 0.6681 |
| 0.6438 | 0.09 | 500 | 0.6524 | 0.3380 | 0.1874 | 0.5004 |
| 0.6028 | 0.11 | 600 | 0.5646 | 0.8004 | 0.5013 | 0.7606 |
| 0.5154 | 0.12 | 700 | 0.5437 | 0.8392 | 0.5576 | 0.7884 |
| 0.5226 | 0.14 | 800 | 0.4823 | 0.8503 | 0.5901 | 0.8024 |
| 0.5104 | 0.16 | 900 | 0.4856 | 0.8452 | 0.5851 | 0.8028 |
| 0.5538 | 0.18 | 1000 | 0.4764 | 0.8478 | 0.5903 | 0.8049 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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