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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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datasets:
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- common_voice
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model-index:
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- name: wav2vec2-base-checkpoint-7.1
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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-checkpoint-7.1
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This model is a fine-tuned version of [jiobiala24/wav2vec2-base-checkpoint-6](https://huggingface.co/jiobiala24/wav2vec2-base-checkpoint-6) on the common_voice dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9369
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- Wer: 0.3243
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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: 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: 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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| 0.3124 | 1.75 | 1000 | 0.5602 | 0.3403 |
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| 0.2428 | 3.5 | 2000 | 0.5924 | 0.3431 |
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| 0.1884 | 5.24 | 3000 | 0.6161 | 0.3423 |
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| 0.1557 | 6.99 | 4000 | 0.6570 | 0.3415 |
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| 0.1298 | 8.74 | 5000 | 0.6837 | 0.3446 |
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| 0.1141 | 10.49 | 6000 | 0.7304 | 0.3396 |
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| 0.1031 | 12.24 | 7000 | 0.7264 | 0.3410 |
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| 0.0916 | 13.99 | 8000 | 0.7229 | 0.3387 |
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| 0.0835 | 15.73 | 9000 | 0.8078 | 0.3458 |
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| 0.0761 | 17.48 | 10000 | 0.8304 | 0.3408 |
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| 0.0693 | 19.23 | 11000 | 0.8290 | 0.3387 |
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| 0.0646 | 20.98 | 12000 | 0.8593 | 0.3372 |
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| 0.0605 | 22.73 | 13000 | 0.8728 | 0.3345 |
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| 0.0576 | 24.48 | 14000 | 0.9111 | 0.3297 |
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| 0.0529 | 26.22 | 15000 | 0.9247 | 0.3273 |
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| 0.0492 | 27.97 | 16000 | 0.9248 | 0.3250 |
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| 0.0472 | 29.72 | 17000 | 0.9369 | 0.3243 |
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### Framework versions
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- Transformers 4.11.3
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- Pytorch 1.10.0+cu111
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- Datasets 1.13.3
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- Tokenizers 0.10.3
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