metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - fleurs
metrics:
  - accuracy
model-index:
  - name: xlm-v-base-language-id
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: fleurs
          type: fleurs
          config: all
          split: validation
          args: all
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9930337861372344

xlm-v-base-language-id

This model is a fine-tuned version of facebook/xlm-v-base on the fleurs dataset. It achieves the following results on the evaluation set:

Loss: 0.0241
Accuracy: 0.9930

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: 3e-05
train_batch_size: 128
eval_batch_size: 128
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 512
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6368	1.0	531	0.4593	0.9689
0.059	2.0	1062	0.0412	0.9899
0.0311	3.0	1593	0.0275	0.9918
0.0255	4.0	2124	0.0243	0.9928
0.017	5.0	2655	0.0241	0.9930

Framework versions

Transformers 4.26.0
Pytorch 1.13.1
Datasets 2.8.0
Tokenizers 0.13.2