---
library_name: transformers
license: apache-2.0
base_model: cis-lmu/glot500-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: glot500-word-dropout-0.1-fr-ca
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# glot500-word-dropout-0.1-fr-ca

This model is a fine-tuned version of [cis-lmu/glot500-base](https://huggingface.co/cis-lmu/glot500-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8141
- Precision: 0.2514
- Recall: 0.1056
- F1: 0.1487
- Accuracy: 0.3548

## 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: 16
- 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: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 2.2926        | 1.0   | 625  | 1.9717          | 0.2099    | 0.0805 | 0.1164 | 0.3179   |
| 1.9299        | 2.0   | 1250 | 1.8141          | 0.2514    | 0.1056 | 0.1487 | 0.3548   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0