---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: 1-epochs8.0-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-epochs8.0-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: 0.5088
- Wer: 0.3569

## 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: 8.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.3362        | 0.69  | 2500  | 3.5583          | 1.0    |
| 2.0051        | 1.37  | 5000  | 1.7739          | 0.9582 |
| 1.159         | 2.06  | 7500  | 0.8389          | 0.6072 |
| 1.0512        | 2.75  | 10000 | 0.6869          | 0.4956 |
| 0.924         | 3.44  | 12500 | 0.6140          | 0.4428 |
| 0.8536        | 4.12  | 15000 | 0.5817          | 0.4121 |
| 0.8607        | 4.81  | 17500 | 0.5506          | 0.3896 |
| 0.8019        | 5.5   | 20000 | 0.5279          | 0.3732 |
| 0.8105        | 6.19  | 22500 | 0.5264          | 0.3612 |
| 0.881         | 6.87  | 25000 | 0.5102          | 0.3605 |
| 0.7724        | 7.56  | 27500 | 0.5088          | 0.3569 |


### Framework versions

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