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--- |
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base_model: Aviral2412/mini_model |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_1_0 |
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metrics: |
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- wer |
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model-index: |
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- name: fineturning-with-pretraining-3 |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: common_voice_1_0 |
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type: common_voice_1_0 |
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config: en |
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split: validation |
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args: en |
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metrics: |
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- name: Wer |
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type: wer |
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value: 1.0000323289796973 |
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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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# fineturning-with-pretraining-3 |
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This model is a fine-tuned version of [Aviral2412/mini_model](https://huggingface.co/Aviral2412/mini_model) on the common_voice_1_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.9160 |
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- Wer: 1.0000 |
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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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| 6.0042 | 4.27 | 500 | 3.1928 | 1.0000 | |
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| 2.9673 | 8.55 | 1000 | 3.0856 | 1.0000 | |
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| 2.9929 | 12.82 | 1500 | 3.0173 | 1.0000 | |
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| 2.9458 | 17.09 | 2000 | 2.9282 | 1.0000 | |
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| 2.9084 | 21.37 | 2500 | 2.9734 | 1.0000 | |
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| 2.8651 | 25.64 | 3000 | 2.9234 | 1.0000 | |
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| 2.8307 | 29.91 | 3500 | 2.9160 | 1.0000 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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