---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: train-bioR-concat-gen1
  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. -->

# train-bioR-concat-gen1

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3226

## 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: 48
- eval_batch_size: 48
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 192
- total_eval_batch_size: 192
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- training_steps: 23848
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.5839        | 0.4193 | 10000 | 1.3249          |
| 0.5677        | 0.8386 | 20000 | 1.3226          |


### Framework versions

- Transformers 4.53.0
- Pytorch 2.5.1
- Datasets 3.6.0
- Tokenizers 0.21.2