---
base_model: AIRI-Institute/gena-lm-bigbird-base-t2t
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: test_run
  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. -->

# test_run

This model is a fine-tuned version of [AIRI-Institute/gena-lm-bigbird-base-t2t](https://huggingface.co/AIRI-Institute/gena-lm-bigbird-base-t2t) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2397
- F1: 0.8195
- Mcc Score: 0.5808
- Accuracy: 0.7933

## 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: 2e-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: constant_with_warmup
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Mcc Score | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:|
| 0.6329        | 1.0   | 94   | 0.5532          | 0.7711 | 0.4531    | 0.7335   |
| 0.4921        | 2.0   | 188  | 0.4789          | 0.8359 | 0.5501    | 0.7832   |
| 0.3981        | 3.0   | 282  | 0.4760          | 0.8347 | 0.5789    | 0.7987   |
| 0.3579        | 4.0   | 376  | 0.6767          | 0.7737 | 0.5377    | 0.7587   |
| 0.2488        | 5.0   | 470  | 0.5478          | 0.8327 | 0.5887    | 0.8015   |
| 0.1889        | 6.0   | 564  | 0.7844          | 0.8231 | 0.5846    | 0.7962   |
| 0.1569        | 7.0   | 658  | 0.8773          | 0.8254 | 0.5868    | 0.7978   |
| 0.1034        | 8.0   | 752  | 1.4445          | 0.7499 | 0.4939    | 0.7353   |
| 0.0832        | 9.0   | 846  | 1.6405          | 0.7195 | 0.4955    | 0.7205   |
| 0.1051        | 10.0  | 940  | 1.2397          | 0.8195 | 0.5808    | 0.7933   |


### Framework versions

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