---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: 1-epochs5-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-epochs5-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: 0.1245
- Wer: 0.0865

## 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: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 40
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 2.8545        | 0.37  | 2500  | 2.8872          | 1.0    |
| 0.7012        | 0.74  | 5000  | 0.3473          | 0.2840 |
| 0.46          | 1.11  | 7500  | 0.2032          | 0.1510 |
| 0.3848        | 1.48  | 10000 | 0.1668          | 0.1194 |
| 0.3535        | 1.85  | 12500 | 0.1518          | 0.1086 |
| 0.3667        | 2.22  | 15000 | 0.1442          | 0.1019 |
| 0.3058        | 2.59  | 17500 | 0.1381          | 0.0961 |
| 0.3026        | 2.96  | 20000 | 0.1327          | 0.0924 |
| 0.2891        | 3.33  | 22500 | 0.1326          | 0.0917 |
| 0.294         | 3.7   | 25000 | 0.1278          | 0.0894 |
| 0.2846        | 4.07  | 27500 | 0.1257          | 0.0885 |
| 0.259         | 4.44  | 30000 | 0.1244          | 0.0874 |
| 0.2348        | 4.81  | 32500 | 0.1245          | 0.0865 |


### Framework versions

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