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--- |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- experiments/data/atcosim_corpus/train |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: 0.0ld_0.05ad_0.05attd_0.0fpd_0.03mtp_10mtl_0.0mfp_10mfl |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# 0.0ld_0.05ad_0.05attd_0.0fpd_0.03mtp_10mtl_0.0mfp_10mfl |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0850 |
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- Wer: 0.0167 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0005 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 96 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 20000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:------:|:-----:|:---------------:|:------:| |
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| 1.4757 | 6.41 | 500 | 0.0614 | 0.0347 | |
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| 0.0624 | 12.82 | 1000 | 0.0525 | 0.0277 | |
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| 0.0388 | 19.23 | 1500 | 0.0693 | 0.0241 | |
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| 0.03 | 25.64 | 2000 | 0.0666 | 0.0244 | |
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| 0.0235 | 32.05 | 2500 | 0.0604 | 0.0260 | |
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| 0.0226 | 38.46 | 3000 | 0.0625 | 0.0230 | |
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| 0.0163 | 44.87 | 3500 | 0.0603 | 0.0195 | |
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| 0.0157 | 51.28 | 4000 | 0.0628 | 0.0209 | |
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| 0.0152 | 57.69 | 4500 | 0.0692 | 0.0238 | |
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| 0.0122 | 64.1 | 5000 | 0.0607 | 0.0210 | |
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| 0.011 | 70.51 | 5500 | 0.0608 | 0.0213 | |
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| 0.0114 | 76.92 | 6000 | 0.0681 | 0.0211 | |
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| 0.0106 | 83.33 | 6500 | 0.0613 | 0.0210 | |
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| 0.0081 | 89.74 | 7000 | 0.0654 | 0.0196 | |
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| 0.0078 | 96.15 | 7500 | 0.0612 | 0.0191 | |
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| 0.0082 | 102.56 | 8000 | 0.0758 | 0.0237 | |
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| 0.0078 | 108.97 | 8500 | 0.0664 | 0.0206 | |
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| 0.0075 | 115.38 | 9000 | 0.0658 | 0.0197 | |
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| 0.0052 | 121.79 | 9500 | 0.0669 | 0.0218 | |
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| 0.0054 | 128.21 | 10000 | 0.0695 | 0.0211 | |
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| 0.0053 | 134.62 | 10500 | 0.0726 | 0.0227 | |
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| 0.0046 | 141.03 | 11000 | 0.0702 | 0.0212 | |
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| 0.0043 | 147.44 | 11500 | 0.0846 | 0.0200 | |
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| 0.0041 | 153.85 | 12000 | 0.0764 | 0.0200 | |
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| 0.0032 | 160.26 | 12500 | 0.0785 | 0.0201 | |
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| 0.0028 | 166.67 | 13000 | 0.0839 | 0.0197 | |
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| 0.0035 | 173.08 | 13500 | 0.0785 | 0.0210 | |
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| 0.0027 | 179.49 | 14000 | 0.0730 | 0.0188 | |
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| 0.002 | 185.9 | 14500 | 0.0794 | 0.0193 | |
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| 0.002 | 192.31 | 15000 | 0.0859 | 0.0211 | |
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| 0.0019 | 198.72 | 15500 | 0.0727 | 0.0183 | |
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| 0.0017 | 205.13 | 16000 | 0.0784 | 0.0187 | |
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| 0.0016 | 211.54 | 16500 | 0.0801 | 0.0196 | |
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| 0.0014 | 217.95 | 17000 | 0.0821 | 0.0185 | |
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| 0.0011 | 224.36 | 17500 | 0.0822 | 0.0176 | |
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| 0.001 | 230.77 | 18000 | 0.0856 | 0.0171 | |
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| 0.001 | 237.18 | 18500 | 0.0792 | 0.0176 | |
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| 0.001 | 243.59 | 19000 | 0.0826 | 0.0173 | |
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| 0.0006 | 250.0 | 19500 | 0.0854 | 0.0170 | |
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| 0.0007 | 256.41 | 20000 | 0.0850 | 0.0167 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.2 |
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