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---
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license: apache-2.0
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tags:
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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: STT_Model_17
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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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# STT_Model_17
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1172
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- Wer: 0.1190
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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: 0.0001
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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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: 1000
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- num_epochs: 50
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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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| 4.1934 | 2.1 | 500 | 3.7998 | 0.9999 |
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| 1.14 | 4.2 | 1000 | 0.4083 | 0.3740 |
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| 0.2217 | 6.3 | 1500 | 0.2515 | 0.2184 |
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| 0.1276 | 8.4 | 2000 | 0.1623 | 0.1803 |
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| 0.0914 | 10.5 | 2500 | 0.1586 | 0.1672 |
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| 0.0731 | 12.61 | 3000 | 0.1648 | 0.1583 |
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| 0.0572 | 14.71 | 3500 | 0.4059 | 0.1534 |
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| 0.054 | 16.81 | 4000 | 0.1694 | 0.1391 |
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| 0.043 | 18.91 | 4500 | 0.1390 | 0.1439 |
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| 0.035 | 21.01 | 5000 | 0.1210 | 0.1362 |
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| 0.0317 | 23.11 | 5500 | 0.1389 | 0.1285 |
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| 0.031 | 25.21 | 6000 | 0.1340 | 0.1316 |
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| 0.0266 | 27.31 | 6500 | 0.1312 | 0.1280 |
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| 0.0209 | 29.41 | 7000 | 0.1484 | 0.1256 |
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| 0.0184 | 31.51 | 7500 | 0.1345 | 0.1289 |
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| 0.0201 | 33.61 | 8000 | 0.1350 | 0.1248 |
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| 0.026 | 35.71 | 8500 | 0.1226 | 0.1235 |
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| 0.016 | 37.82 | 9000 | 0.1235 | 0.1232 |
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| 0.0115 | 39.92 | 9500 | 0.1223 | 0.1216 |
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| 0.013 | 42.02 | 10000 | 0.1314 | 0.1206 |
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| 0.0225 | 44.12 | 10500 | 0.1158 | 0.1211 |
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| 0.011 | 46.22 | 11000 | 0.1181 | 0.1203 |
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| 0.0106 | 48.32 | 11500 | 0.1172 | 0.1190 |
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### Framework versions
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- Transformers 4.27.3
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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