---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: roberta-large-tqacd
  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. -->

# roberta-large-tqacd

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8956
- F1 Macro: 0.2608
- Precision: 0.3007
- Recall: 0.2456
- Accuracy: 0.4158

## 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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro | Precision | Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| No log        | 1.0   | 114  | 2.4069          | 0.0094   | 0.0050    | 0.0909 | 0.0545   |
| No log        | 2.0   | 228  | 2.3298          | 0.1595   | 0.2519    | 0.1597 | 0.3366   |
| No log        | 3.0   | 342  | 2.2454          | 0.1746   | 0.2033    | 0.2052 | 0.2475   |
| No log        | 4.0   | 456  | 2.1684          | 0.2588   | 0.2830    | 0.2813 | 0.3614   |
| 2.2272        | 5.0   | 570  | 2.3380          | 0.2425   | 0.2709    | 0.2786 | 0.3515   |
| 2.2272        | 6.0   | 684  | 2.4213          | 0.3017   | 0.3142    | 0.3231 | 0.3713   |
| 2.2272        | 7.0   | 798  | 2.7961          | 0.3100   | 0.3442    | 0.3141 | 0.3911   |
| 2.2272        | 8.0   | 912  | 3.0757          | 0.2478   | 0.2576    | 0.2722 | 0.3614   |
| 0.6491        | 9.0   | 1026 | 3.8956          | 0.2608   | 0.3007    | 0.2456 | 0.4158   |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1