---
library_name: transformers
license: mit
base_model: vblagoje/bart_lfqa
tags:
- generated_from_trainer
model-index:
- name: BART_HYDROGEN_GENERATION_QA
  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. -->

# BART_HYDROGEN_GENERATION_QA

This model is a fine-tuned version of [vblagoje/bart_lfqa](https://huggingface.co/vblagoje/bart_lfqa) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5046

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 8

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.2697        | 0.2092 | 100  | 0.5574          |
| 1.0628        | 0.4184 | 200  | 0.5151          |
| 1.0037        | 0.6276 | 300  | 0.5066          |
| 0.9652        | 0.8368 | 400  | 0.4842          |
| 0.9284        | 1.0460 | 500  | 0.4974          |
| 0.8272        | 1.2552 | 600  | 0.5046          |


### Framework versions

- Transformers 4.46.0
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1