---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: experiment_lr_20241215_145438-postcrash
  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_20241215_145438-postcrash

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: 0.0166
- Exact Match Accuracy: 0.5777

## 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: 32
- eval_batch_size: 32
- seed: 42
- 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: 500
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Exact Match Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------------------:|
| 0.0725        | 1.0   | 2297  | 0.0720          | 0.0                  |
| 0.0661        | 2.0   | 4594  | 0.0607          | 0.0                  |
| 0.0422        | 3.0   | 6891  | 0.0356          | 0.0245               |
| 0.0252        | 4.0   | 9188  | 0.0234          | 0.1441               |
| 0.0193        | 5.0   | 11485 | 0.0185          | 0.4620               |
| 0.0164        | 6.0   | 13782 | 0.0168          | 0.5711               |
| 0.0158        | 7.0   | 16079 | 0.0166          | 0.5777               |


### Framework versions

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