---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: 1-epochs61.0-char-based-freeze_cnn-dropout0.1
  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. -->

# 1-epochs61.0-char-based-freeze_cnn-dropout0.1

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co./facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0164
- Wer: 0.5324

## 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: 10
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 40
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 61.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.4352        | 5.11  | 2500  | 3.6464          | 1.0    |
| 1.9084        | 10.22 | 5000  | 1.7450          | 0.9275 |
| 1.0531        | 15.34 | 7500  | 1.1180          | 0.6646 |
| 0.8217        | 20.45 | 10000 | 1.1415          | 0.6048 |
| 0.7405        | 25.56 | 12500 | 1.0814          | 0.5776 |
| 0.6432        | 30.67 | 15000 | 1.0632          | 0.5611 |
| 0.6507        | 35.79 | 17500 | 1.0200          | 0.5427 |
| 0.5533        | 40.9  | 20000 | 1.0019          | 0.5367 |
| 0.561         | 46.01 | 22500 | 1.0246          | 0.5392 |
| 0.5292        | 51.12 | 25000 | 0.9992          | 0.5245 |
| 0.5085        | 56.24 | 27500 | 1.0164          | 0.5324 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.14.1