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update model card README.md
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README.md
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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: wav2vec2-base-timit-eng
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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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# wav2vec2-base-timit-eng
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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: 0.4391
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- Wer: 0.3836
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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: 30
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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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| 3.8306 | 1.0 | 500 | 2.9588 | 1.0 |
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| 2.1928 | 2.01 | 1000 | 1.2215 | 0.9355 |
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| 1.1547 | 3.01 | 1500 | 0.9228 | 0.7135 |
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| 0.9487 | 4.02 | 2000 | 0.7682 | 0.6513 |
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| 0.8163 | 5.02 | 2500 | 0.7154 | 0.6164 |
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| 0.6642 | 6.02 | 3000 | 0.6160 | 0.5919 |
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| 0.6291 | 7.03 | 3500 | 0.6224 | 0.5485 |
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| 0.601 | 8.03 | 4000 | 0.5927 | 0.5371 |
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| 0.5443 | 9.04 | 4500 | 0.5757 | 0.5240 |
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| 0.4798 | 10.04 | 5000 | 0.5673 | 0.5074 |
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| 0.5142 | 11.04 | 5500 | 0.6138 | 0.5131 |
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| 0.4044 | 12.05 | 6000 | 0.5899 | 0.5120 |
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| 0.4214 | 13.05 | 6500 | 0.5443 | 0.4932 |
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| 0.377 | 14.06 | 7000 | 0.6055 | 0.5337 |
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| 0.3985 | 15.06 | 7500 | 0.5055 | 0.4812 |
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| 0.3609 | 16.06 | 8000 | 0.5764 | 0.4600 |
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| 0.299 | 17.07 | 8500 | 0.5524 | 0.4635 |
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| 0.2984 | 18.07 | 9000 | 0.5272 | 0.4435 |
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| 0.2908 | 19.08 | 9500 | 0.5393 | 0.4446 |
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| 0.2714 | 20.08 | 10000 | 0.4548 | 0.4463 |
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| 0.2285 | 21.08 | 10500 | 0.5126 | 0.4309 |
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| 0.2245 | 22.09 | 11000 | 0.4770 | 0.4309 |
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| 0.229 | 23.09 | 11500 | 0.4763 | 0.4150 |
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| 0.2032 | 24.1 | 12000 | 0.5009 | 0.4127 |
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| 0.2125 | 25.1 | 12500 | 0.4698 | 0.4087 |
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| 0.1955 | 26.1 | 13000 | 0.4592 | 0.4001 |
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| 0.1841 | 27.11 | 13500 | 0.4517 | 0.3898 |
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| 0.164 | 28.11 | 14000 | 0.4628 | 0.3927 |
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| 0.1687 | 29.12 | 14500 | 0.4391 | 0.3836 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.0+cu116
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- Datasets 1.18.3
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- Tokenizers 0.13.2
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