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README.md
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---
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license: apache-2.0
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base_model: facebook/wav2vec2-base
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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: w2v2-base-pretrained_lr5e-5_at0.8_da0.2
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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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# w2v2-base-pretrained_lr5e-5_at0.8_da0.2
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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: 1.6497
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- Wer: 0.2191
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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: 5e-05
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- train_batch_size: 32
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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: 500
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- training_steps: 4000
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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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| 19.3673 | 25.0 | 250 | 3.5485 | 1.0 |
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| 3.1951 | 50.0 | 500 | 3.0982 | 1.0 |
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| 2.9571 | 75.0 | 750 | 2.5890 | 1.0 |
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| 0.8132 | 100.0 | 1000 | 1.0110 | 0.4161 |
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| 0.0936 | 125.0 | 1250 | 1.4372 | 0.2636 |
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| 0.0487 | 150.0 | 1500 | 1.4519 | 0.2533 |
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| 0.0314 | 175.0 | 1750 | 1.5135 | 0.2554 |
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| 0.0204 | 200.0 | 2000 | 1.6471 | 0.2439 |
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| 0.0189 | 225.0 | 2250 | 1.5987 | 0.2405 |
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| 0.013 | 250.0 | 2500 | 1.7187 | 0.2251 |
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| 0.0109 | 275.0 | 2750 | 1.6743 | 0.2302 |
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| 0.0099 | 300.0 | 3000 | 1.6391 | 0.2200 |
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| 0.0084 | 325.0 | 3250 | 1.6393 | 0.2200 |
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| 0.0074 | 350.0 | 3500 | 1.7161 | 0.2136 |
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| 0.0066 | 375.0 | 3750 | 1.6937 | 0.2170 |
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| 0.0063 | 400.0 | 4000 | 1.6497 | 0.2191 |
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### Framework versions
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- Transformers 4.35.0
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- Pytorch 2.0.0
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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model.safetensors
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