---
base_model: /gpfs/home/ikuzmin/hier-bert-pytorch/data/hier-model
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hier-bert-i3-mlm2
  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. -->

# hier-bert-i3-mlm2

This model is a fine-tuned version of [/gpfs/home/ikuzmin/hier-bert-pytorch/data/hier-model](https://huggingface.co//gpfs/home/ikuzmin/hier-bert-pytorch/data/hier-model) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2929
- Accuracy: 0.5612

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.5
- training_steps: 50000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.9488        | 1.55  | 25000 | 2.7667          | 0.4935   |
| 2.4233        | 3.1   | 50000 | 2.2922          | 0.5612   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3