---
base_model: facebook/wav2vec2-xls-r-300m
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-300m-tsovatush-demo-colab-bryn-hauk-8-6
  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. -->

# wav2vec2-large-xls-r-300m-tsovatush-demo-colab-bryn-hauk-8-6

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4337
- Wer: 0.5188

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 5.3164        | 4.1667  | 400  | 3.2339          | None   |
| 2.1905        | 8.3333  | 800  | 1.1741          | 0.6596 |
| 1.2308        | 12.5    | 1200 | 1.1192          | 0.6275 |
| 0.8868        | 16.6667 | 1600 | 1.1354          | 0.5776 |
| 0.6593        | 20.8333 | 2000 | 1.2042          | 0.5831 |
| 0.466         | 25.0    | 2400 | 1.3671          | 0.5654 |
| 0.3319        | 29.1667 | 2800 | 1.3642          | 0.5388 |
| 0.2511        | 33.3333 | 3200 | 1.3517          | 0.5621 |
| 0.1895        | 37.5    | 3600 | 1.3898          | 0.5366 |
| 0.1413        | 41.6667 | 4000 | 1.4396          | 0.5277 |
| 0.1086        | 45.8333 | 4400 | 1.4229          | 0.5344 |
| 0.0897        | 50.0    | 4800 | 1.4337          | 0.5188 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 1.18.3
- Tokenizers 0.19.1