---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: working
  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. -->

# working

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: 0.2536
- Wer: 0.5805
- Cer: 0.0690

## 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: 3e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- training_steps: 26000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 2.0464        | 1.49  | 1000  | 1.5865          | 0.9968 | 0.5743 |
| 1.2779        | 2.98  | 2000  | 0.4195          | 0.7539 | 0.1008 |
| 1.0865        | 4.46  | 3000  | 0.3272          | 0.6791 | 0.0852 |
| 1.0852        | 5.95  | 4000  | 0.3039          | 0.6409 | 0.0789 |
| 1.0193        | 7.44  | 5000  | 0.3009          | 0.6442 | 0.0809 |
| 0.9566        | 8.93  | 6000  | 0.2804          | 0.6182 | 0.0762 |
| 0.9086        | 10.42 | 7000  | 0.2842          | 0.6336 | 0.0772 |
| 0.9161        | 11.9  | 8000  | 0.2757          | 0.6044 | 0.0735 |
| 0.8569        | 13.39 | 9000  | 0.2809          | 0.6052 | 0.0748 |
| 0.8517        | 14.88 | 10000 | 0.2813          | 0.6166 | 0.0759 |
| 0.8304        | 16.37 | 11000 | 0.2808          | 0.6044 | 0.0759 |
| 0.8325        | 17.86 | 12000 | 0.2656          | 0.6060 | 0.0735 |
| 0.7918        | 19.35 | 13000 | 0.2676          | 0.5930 | 0.0730 |
| 0.8061        | 20.83 | 14000 | 0.2740          | 0.5890 | 0.0731 |
| 0.7206        | 22.32 | 15000 | 0.2735          | 0.6141 | 0.0730 |
| 0.7372        | 23.81 | 16000 | 0.2663          | 0.5857 | 0.0711 |
| 0.7285        | 25.3  | 17000 | 0.2708          | 0.5841 | 0.0723 |
| 0.6778        | 26.79 | 18000 | 0.2726          | 0.5825 | 0.0724 |
| 0.7117        | 28.27 | 19000 | 0.2737          | 0.5898 | 0.0723 |
| 0.6951        | 29.76 | 20000 | 0.2733          | 0.5890 | 0.0721 |
| 0.6775        | 31.25 | 21000 | 0.2721          | 0.5865 | 0.0725 |
| 0.666         | 32.74 | 22000 | 0.2733          | 0.5857 | 0.0721 |
| 0.688         | 34.23 | 23000 | 0.2700          | 0.5890 | 0.0718 |
| 0.6813        | 35.71 | 24000 | 0.2724          | 0.5930 | 0.0717 |
| 0.6409        | 37.2  | 25000 | 0.2704          | 0.5922 | 0.0714 |
| 0.6427        | 38.69 | 26000 | 0.2704          | 0.5881 | 0.0713 |


### Framework versions

- Transformers 4.17.0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0