---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: mrc-xlmr-base-dsc
  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. -->

# mrc-xlmr-base-dsc

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7023
- Precision: 0.7109
- Recall: 0.6810
- F1: 0.6767
- Exact Match: 0.7123

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Exact Match |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:-----------:|
| 0.7291        | 1.0   | 3180  | 0.6487          | 0.6459    | 0.5921 | 0.5958 | 0.6368      |
| 0.612         | 2.0   | 6360  | 0.5966          | 0.7004    | 0.6382 | 0.6449 | 0.6793      |
| 0.4627        | 3.0   | 9540  | 0.6061          | 0.6920    | 0.6645 | 0.6573 | 0.6949      |
| 0.3604        | 4.0   | 12720 | 0.6453          | 0.6895    | 0.6795 | 0.6652 | 0.7054      |
| 0.2852        | 5.0   | 15900 | 0.7023          | 0.7109    | 0.6810 | 0.6767 | 0.7123      |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2