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---
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: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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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
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