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

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: 1.6559

## 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: 24
- eval_batch_size: 24
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 96
- total_eval_batch_size: 96
- 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: 41803
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 1.2076        | 0.0239 | 1000  | 1.8223          |
| 1.2901        | 0.0478 | 2000  | 1.8245          |
| 1.1528        | 0.0718 | 3000  | 1.8674          |
| 1.0056        | 0.0957 | 4000  | 1.9692          |
| 0.8399        | 0.1196 | 5000  | 2.0165          |
| 0.7892        | 0.1435 | 6000  | 1.9441          |
| 0.7658        | 0.1674 | 7000  | 1.8904          |
| 0.7284        | 0.1914 | 8000  | 1.8260          |
| 0.7217        | 0.2153 | 9000  | 1.8162          |
| 0.7122        | 0.2392 | 10000 | 1.7559          |
| 0.7055        | 0.2631 | 11000 | 1.7974          |
| 0.6943        | 0.2871 | 12000 | 1.7621          |
| 0.6942        | 0.3110 | 13000 | 1.7651          |
| 0.6868        | 0.3349 | 14000 | 1.7228          |
| 0.6817        | 0.3588 | 15000 | 1.7558          |
| 0.6911        | 0.3827 | 16000 | 1.7466          |
| 0.6889        | 0.4067 | 17000 | 1.7291          |
| 0.6798        | 0.4306 | 18000 | 1.6921          |
| 0.675         | 0.4545 | 19000 | 1.7139          |
| 0.6779        | 0.4784 | 20000 | 1.6933          |
| 0.6851        | 0.5023 | 21000 | 1.7136          |
| 0.675         | 0.5263 | 22000 | 1.6874          |
| 0.6747        | 0.5502 | 23000 | 1.6950          |
| 0.6724        | 0.5741 | 24000 | 1.6884          |
| 0.6631        | 0.5980 | 25000 | 1.6873          |
| 0.6671        | 0.6220 | 26000 | 1.6983          |
| 0.6645        | 0.6459 | 27000 | 1.6729          |
| 0.658         | 0.6698 | 28000 | 1.6809          |
| 0.6605        | 0.6937 | 29000 | 1.6656          |
| 0.6599        | 0.7176 | 30000 | 1.6704          |
| 0.6591        | 0.7416 | 31000 | 1.6679          |
| 0.6664        | 0.7655 | 32000 | 1.6555          |
| 0.6608        | 0.7894 | 33000 | 1.6487          |
| 0.6609        | 0.8133 | 34000 | 1.6522          |
| 0.6553        | 0.8372 | 35000 | 1.6502          |
| 0.6527        | 0.8612 | 36000 | 1.6568          |
| 0.6648        | 0.8851 | 37000 | 1.6587          |
| 0.6515        | 0.9090 | 38000 | 1.6471          |
| 0.65          | 0.9329 | 39000 | 1.6461          |
| 0.65          | 0.9568 | 40000 | 1.6499          |
| 0.6533        | 0.9808 | 41000 | 1.6559          |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0