---
license: apache-2.0
tags:
- automatic-speech-recognition
- experiments/data/atcosim_corpus/train
- generated_from_trainer
metrics:
- wer
model-index:
- name: 0.0ld_0.05ad_0.05attd_0.0fpd_0.03mtp_10mtl_0.0mfp_10mfl
  results: []
---

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# 0.0ld_0.05ad_0.05attd_0.0fpd_0.03mtp_10mtl_0.0mfp_10mfl

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the EXPERIMENTS/DATA/ATCOSIM_CORPUS/TRAIN - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0988
- Wer: 0.0736

## 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: 0.0005
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 1.9105        | 6.41   | 500   | 0.1622          | 0.1531 |
| 0.1119        | 12.82  | 1000  | 0.0971          | 0.0936 |
| 0.0614        | 19.23  | 1500  | 0.1002          | 0.0983 |
| 0.044         | 25.64  | 2000  | 0.1011          | 0.0929 |
| 0.0366        | 32.05  | 2500  | 0.0932          | 0.0828 |
| 0.0315        | 38.46  | 3000  | 0.0926          | 0.0880 |
| 0.0297        | 44.87  | 3500  | 0.0972          | 0.0882 |
| 0.0216        | 51.28  | 4000  | 0.0911          | 0.0774 |
| 0.0211        | 57.69  | 4500  | 0.0982          | 0.0891 |
| 0.0187        | 64.1   | 5000  | 0.1009          | 0.0863 |
| 0.02          | 70.51  | 5500  | 0.0953          | 0.0852 |
| 0.0163        | 76.92  | 6000  | 0.1028          | 0.0804 |
| 0.0128        | 83.33  | 6500  | 0.0930          | 0.0856 |
| 0.0127        | 89.74  | 7000  | 0.0892          | 0.0676 |
| 0.0116        | 96.15  | 7500  | 0.0857          | 0.0753 |
| 0.0139        | 102.56 | 8000  | 0.1078          | 0.0481 |
| 0.0107        | 108.97 | 8500  | 0.0955          | 0.0683 |
| 0.0096        | 115.38 | 9000  | 0.0846          | 0.0697 |
| 0.0089        | 121.79 | 9500  | 0.0854          | 0.0675 |
| 0.0084        | 128.21 | 10000 | 0.0875          | 0.0779 |
| 0.0074        | 134.62 | 10500 | 0.0840          | 0.0770 |
| 0.0061        | 141.03 | 11000 | 0.0903          | 0.0754 |
| 0.0076        | 147.44 | 11500 | 0.0872          | 0.0769 |
| 0.0069        | 153.85 | 12000 | 0.0891          | 0.0772 |
| 0.0061        | 160.26 | 12500 | 0.0971          | 0.0774 |
| 0.0049        | 166.67 | 13000 | 0.0984          | 0.0726 |
| 0.0045        | 173.08 | 13500 | 0.0952          | 0.0765 |
| 0.0039        | 179.49 | 14000 | 0.1015          | 0.0762 |
| 0.0031        | 185.9  | 14500 | 0.0937          | 0.0712 |
| 0.0032        | 192.31 | 15000 | 0.0982          | 0.0635 |
| 0.0028        | 198.72 | 15500 | 0.0981          | 0.0743 |
| 0.0024        | 205.13 | 16000 | 0.1019          | 0.0712 |
| 0.0024        | 211.54 | 16500 | 0.0957          | 0.0732 |
| 0.002         | 217.95 | 17000 | 0.0941          | 0.0732 |
| 0.0015        | 224.36 | 17500 | 0.1009          | 0.0717 |
| 0.0017        | 230.77 | 18000 | 0.0955          | 0.0730 |
| 0.0013        | 237.18 | 18500 | 0.0989          | 0.0732 |
| 0.0013        | 243.59 | 19000 | 0.0967          | 0.0738 |
| 0.0011        | 250.0  | 19500 | 0.0980          | 0.0734 |
| 0.0008        | 256.41 | 20000 | 0.0988          | 0.0736 |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.6.1
- Tokenizers 0.13.2