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--- |
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language: |
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- eng |
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license: apache-2.0 |
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tags: |
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- '[finetuned_model, lj_speech11]' |
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- generated_from_trainer |
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base_model: facebook/wav2vec2-base-960h |
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datasets: |
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- FYP/LJ-SpeechLJ |
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model-index: |
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- name: SpeechT5 STT Wav2Vec2 |
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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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# SpeechT5 STT Wav2Vec2 |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the Lj-Speech dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 491.2500 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 100 |
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- num_epochs: 5 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 494.9709 | 0.3795 | 50 | 486.0701 | |
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| 534.2352 | 0.7590 | 100 | 488.7172 | |
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| 816.0739 | 1.1385 | 150 | 490.4418 | |
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| 566.1295 | 1.5180 | 200 | 504.5211 | |
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| 586.0909 | 1.8975 | 250 | 489.5141 | |
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| 601.5043 | 2.2770 | 300 | 486.6875 | |
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| 487.8737 | 2.6565 | 350 | 489.5807 | |
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| 1145.4591 | 3.0361 | 400 | 511.4276 | |
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| 686.6008 | 3.4156 | 450 | 496.0722 | |
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| 664.612 | 3.7951 | 500 | 486.9992 | |
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| 630.4309 | 4.1746 | 550 | 500.0555 | |
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| 513.7977 | 4.5541 | 600 | 488.6891 | |
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| 494.3428 | 4.9336 | 650 | 491.2500 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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