transformers pytorch xlm-roberta token-classification generated_from_trainer dataset:pharmaconer base_model:FacebookAI/xlm-roberta-base base_model:finetune:FacebookAI/xlm-roberta-base license:mit autotrain_compatible endpoints_compatible region:us
---
base_model: xlm-roberta-base
datasets:
- pharmaconer
license: mit
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base-pharmaconer
  results: []
---

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# xlm-roberta-base-pharmaconer

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the pharmaconer dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0243
- F1 Score: 1.0

## 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: 5e-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 | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0458        | 1.0   | 1017 | 0.0344          | 1.0      |
| 0.0225        | 2.0   | 2034 | 0.0254          | 1.0      |
| 0.0114        | 3.0   | 3051 | 0.0203          | 1.0      |
| 0.0065        | 4.0   | 4068 | 0.0216          | 1.0      |
| 0.0035        | 5.0   | 5085 | 0.0243          | 1.0      |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3
