---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: M_gpt_v1.3
  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. -->

# M_gpt_v1.3

This model is a fine-tuned version of [ai-forever/mGPT](https://huggingface.co/ai-forever/mGPT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4547
- Precision: 0.56
- Recall: 0.3739
- F1: 0.4484
- Accuracy: 0.9076

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4869        | 1.0   | 882  | 0.3957          | 0.5886    | 0.2987 | 0.3963 | 0.8995   |
| 0.3467        | 2.0   | 1764 | 0.3723          | 0.5572    | 0.3696 | 0.4444 | 0.9033   |
| 0.3031        | 3.0   | 2646 | 0.3709          | 0.5917    | 0.3289 | 0.4228 | 0.9082   |
| 0.2786        | 4.0   | 3528 | 0.3928          | 0.5649    | 0.3760 | 0.4515 | 0.9069   |
| 0.2629        | 5.0   | 4410 | 0.4547          | 0.56      | 0.3739 | 0.4484 | 0.9076   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3