---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: experiment_lr_20241214_183914
  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. -->

# experiment_lr_20241214_183914

This model is a fine-tuned version of [roberta-base](https://huggingface.co./roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1307
- Exact Match Accuracy: 0.0

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Exact Match Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| No log        | 1.0   | 288  | 0.1307          | 0.0                  |
| 0.2773        | 2.0   | 576  | 0.0782          | 0.0                  |
| 0.2773        | 3.0   | 864  | 0.0732          | 0.0                  |
| 0.0756        | 4.0   | 1152 | 0.0723          | 0.0                  |


### Framework versions

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