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---
base_model: AIRI-Institute/gena-lm-bert-base-lastln-t2t
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: gut_1024-finetuned-lora-bert-base-lastln-t2t
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-lastln-t2t
This model is a fine-tuned version of [AIRI-Institute/gena-lm-bert-base-lastln-t2t](https://huggingface.co/AIRI-Institute/gena-lm-bert-base-lastln-t2t) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4049
- F1: 0.8657
- Mcc Score: 0.6421
- Accuracy: 0.8290
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:|
| 0.6139 | 0.02 | 100 | 0.5419 | 0.7847 | 0.4843 | 0.7487 |
| 0.5575 | 0.04 | 200 | 0.5407 | 0.7875 | 0.4941 | 0.7530 |
| 0.5339 | 0.05 | 300 | 0.5027 | 0.8347 | 0.5669 | 0.7943 |
| 0.4807 | 0.07 | 400 | 0.4584 | 0.8551 | 0.6032 | 0.8053 |
| 0.5071 | 0.09 | 500 | 0.4408 | 0.8583 | 0.6192 | 0.8180 |
| 0.4011 | 0.11 | 600 | 0.4346 | 0.8576 | 0.6127 | 0.8129 |
| 0.4133 | 0.12 | 700 | 0.4694 | 0.8461 | 0.6007 | 0.8100 |
| 0.424 | 0.14 | 800 | 0.4073 | 0.8651 | 0.6357 | 0.8239 |
| 0.4084 | 0.16 | 900 | 0.3974 | 0.8677 | 0.6429 | 0.8264 |
| 0.4427 | 0.18 | 1000 | 0.4049 | 0.8657 | 0.6421 | 0.8290 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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