---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: 1-epochs12.0-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-epochs12.0-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: nan
- Wer: 1.0

## 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: 12.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:---:|
| 3.6685        | 1.03  | 2500  | 4.0882          | 1.0 |
| 3.6718        | 2.06  | 5000  | 4.0882          | 1.0 |
| 3.6684        | 3.1   | 7500  | 4.0882          | 1.0 |
| 0.0           | 4.13  | 10000 | nan             | 1.0 |
| 0.0           | 5.16  | 12500 | nan             | 1.0 |
| 0.0           | 6.19  | 15000 | nan             | 1.0 |
| 0.0           | 7.22  | 17500 | nan             | 1.0 |
| 0.0           | 8.25  | 20000 | nan             | 1.0 |
| 0.0           | 9.29  | 22500 | nan             | 1.0 |
| 0.0           | 10.32 | 25000 | nan             | 1.0 |
| 0.0           | 11.35 | 27500 | nan             | 1.0 |


### Framework versions

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