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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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- automatic-speech-recognition |
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- timit_asr |
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- generated_from_trainer |
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datasets: |
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- timit_asr |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-base-timit-fine-tuned |
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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: TIMIT_ASR - NA |
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type: timit_asr |
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config: clean |
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split: test |
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args: 'Config: na, Training split: train, Eval split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.4328507693708459 |
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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-fine-tuned |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the TIMIT_ASR - NA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4233 |
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- Wer: 0.4329 |
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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: 64 |
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- eval_batch_size: 32 |
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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: 20.0 |
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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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| 3.158 | 1.7241 | 100 | 3.6803 | 1.0 | |
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| 2.9744 | 3.4483 | 200 | 3.1165 | 1.0 | |
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| 2.9266 | 5.1724 | 300 | 3.0175 | 1.0 | |
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| 2.1336 | 6.8966 | 400 | 2.2135 | 1.0117 | |
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| 1.0119 | 8.6207 | 500 | 1.0227 | 0.8251 | |
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| 0.4995 | 10.3448 | 600 | 0.7700 | 0.6574 | |
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| 0.3233 | 12.0690 | 700 | 0.4970 | 0.5241 | |
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| 0.2452 | 13.7931 | 800 | 0.4585 | 0.4908 | |
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| 0.181 | 15.5172 | 900 | 0.4626 | 0.4814 | |
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| 0.1419 | 17.2414 | 1000 | 0.4917 | 0.4775 | |
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| 0.1175 | 18.9655 | 1100 | 0.4279 | 0.4359 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.3.0a0+gitcd033a1 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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