---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xtreme_s
metrics:
- accuracy
model-index:
- name: xtreme_s_xlsr_300m_fleurs_langid_truncated
  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. -->

# xtreme_s_xlsr_300m_fleurs_langid_truncated

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the xtreme_s dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.7236
- Loss: 1.3514

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.5296        | 0.26  | 1000  | 0.4016   | 2.6633          |
| 0.4252        | 0.52  | 2000  | 0.5751   | 1.8582          |
| 0.2989        | 0.78  | 3000  | 0.6332   | 1.6780          |
| 0.3563        | 1.04  | 4000  | 0.6799   | 1.4479          |
| 0.1617        | 1.3   | 5000  | 0.6679   | 1.5066          |
| 0.1409        | 1.56  | 6000  | 0.6992   | 1.4082          |
| 0.01          | 1.82  | 7000  | 0.7071   | 1.2448          |
| 0.0018        | 2.08  | 8000  | 0.7148   | 1.1996          |
| 0.0014        | 2.34  | 9000  | 0.6410   | 1.6505          |
| 0.0188        | 2.6   | 10000 | 0.6840   | 1.4050          |
| 0.0007        | 2.86  | 11000 | 0.6621   | 1.5831          |
| 0.1038        | 3.12  | 12000 | 0.6829   | 1.5441          |
| 0.0003        | 3.38  | 13000 | 0.6900   | 1.3483          |
| 0.0004        | 3.64  | 14000 | 0.6414   | 1.7070          |
| 0.0003        | 3.9   | 15000 | 0.7075   | 1.3198          |
| 0.0002        | 4.16  | 16000 | 0.7105   | 1.3118          |
| 0.0001        | 4.42  | 17000 | 0.7029   | 1.4099          |
| 0.0           | 4.68  | 18000 | 0.7180   | 1.3658          |
| 0.0001        | 4.93  | 19000 | 0.7236   | 1.3514          |


### Framework versions

- Transformers 4.18.0.dev0
- Pytorch 1.10.1+cu111
- Datasets 1.18.4.dev0
- Tokenizers 0.11.6