---
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-large-960h-lv60-self](https://huggingface.co/facebook/wav2vec2-large-960h-lv60-self) on the EXPERIMENTS/DATA/ATCOSIM_CORPUS/TRAIN - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0850
- Wer: 0.0167

## 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    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 1.4757        | 6.41   | 500   | 0.0614          | 0.0347 |
| 0.0624        | 12.82  | 1000  | 0.0525          | 0.0277 |
| 0.0388        | 19.23  | 1500  | 0.0693          | 0.0241 |
| 0.03          | 25.64  | 2000  | 0.0666          | 0.0244 |
| 0.0235        | 32.05  | 2500  | 0.0604          | 0.0260 |
| 0.0226        | 38.46  | 3000  | 0.0625          | 0.0230 |
| 0.0163        | 44.87  | 3500  | 0.0603          | 0.0195 |
| 0.0157        | 51.28  | 4000  | 0.0628          | 0.0209 |
| 0.0152        | 57.69  | 4500  | 0.0692          | 0.0238 |
| 0.0122        | 64.1   | 5000  | 0.0607          | 0.0210 |
| 0.011         | 70.51  | 5500  | 0.0608          | 0.0213 |
| 0.0114        | 76.92  | 6000  | 0.0681          | 0.0211 |
| 0.0106        | 83.33  | 6500  | 0.0613          | 0.0210 |
| 0.0081        | 89.74  | 7000  | 0.0654          | 0.0196 |
| 0.0078        | 96.15  | 7500  | 0.0612          | 0.0191 |
| 0.0082        | 102.56 | 8000  | 0.0758          | 0.0237 |
| 0.0078        | 108.97 | 8500  | 0.0664          | 0.0206 |
| 0.0075        | 115.38 | 9000  | 0.0658          | 0.0197 |
| 0.0052        | 121.79 | 9500  | 0.0669          | 0.0218 |
| 0.0054        | 128.21 | 10000 | 0.0695          | 0.0211 |
| 0.0053        | 134.62 | 10500 | 0.0726          | 0.0227 |
| 0.0046        | 141.03 | 11000 | 0.0702          | 0.0212 |
| 0.0043        | 147.44 | 11500 | 0.0846          | 0.0200 |
| 0.0041        | 153.85 | 12000 | 0.0764          | 0.0200 |
| 0.0032        | 160.26 | 12500 | 0.0785          | 0.0201 |
| 0.0028        | 166.67 | 13000 | 0.0839          | 0.0197 |
| 0.0035        | 173.08 | 13500 | 0.0785          | 0.0210 |
| 0.0027        | 179.49 | 14000 | 0.0730          | 0.0188 |
| 0.002         | 185.9  | 14500 | 0.0794          | 0.0193 |
| 0.002         | 192.31 | 15000 | 0.0859          | 0.0211 |
| 0.0019        | 198.72 | 15500 | 0.0727          | 0.0183 |
| 0.0017        | 205.13 | 16000 | 0.0784          | 0.0187 |
| 0.0016        | 211.54 | 16500 | 0.0801          | 0.0196 |
| 0.0014        | 217.95 | 17000 | 0.0821          | 0.0185 |
| 0.0011        | 224.36 | 17500 | 0.0822          | 0.0176 |
| 0.001         | 230.77 | 18000 | 0.0856          | 0.0171 |
| 0.001         | 237.18 | 18500 | 0.0792          | 0.0176 |
| 0.001         | 243.59 | 19000 | 0.0826          | 0.0173 |
| 0.0006        | 250.0  | 19500 | 0.0854          | 0.0170 |
| 0.0007        | 256.41 | 20000 | 0.0850          | 0.0167 |


### Framework versions

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