---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-xls-r-300m
datasets:
- ml-superb-subset
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-ml-superb-xty
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: ml-superb-subset
      type: ml-superb-subset
      config: xty
      split: test
      args: xty
    metrics:
    - type: wer
      value: 0.8114393463230672
      name: Wer
---

<!-- 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. -->

# wav2vec2-large-xls-r-300m-ml-superb-xty

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the ml-superb-subset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6099
- Wer: 0.8114

## 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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 3.1825        | 0.8219 | 30   | 3.2071          | 1.0    |
| 3.0491        | 1.6438 | 60   | 3.0508          | 1.0    |
| 2.9717        | 2.4658 | 90   | 3.0385          | 1.0    |
| 2.93          | 3.2877 | 120  | 2.9222          | 1.0    |
| 2.6444        | 4.1096 | 150  | 2.3753          | 0.9931 |
| 2.05          | 4.9315 | 180  | 1.9591          | 0.9868 |
| 1.6856        | 5.7534 | 210  | 1.7810          | 0.9478 |
| 1.4182        | 6.5753 | 240  | 1.6843          | 0.8843 |
| 1.1773        | 7.3973 | 270  | 1.6370          | 0.8554 |
| 1.0521        | 8.2192 | 300  | 1.5868          | 0.8215 |
| 0.881         | 9.0411 | 330  | 1.5935          | 0.8202 |
| 0.7605        | 9.8630 | 360  | 1.6099          | 0.8114 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1