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End of training

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  1. README.md +89 -0
  2. generation_config.json +190 -0
  3. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ language:
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+ - en
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+ base_model: distil-small.en
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - librispeech_asr
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: DistilFT-English-10h
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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: librispeech
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+ type: librispeech_asr
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+ config: default
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+ split: None
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+ args: 'config: en, split: test-clean'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 4.4905114250188545
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+ ---
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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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+
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+ # DistilFT-English-10h
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+
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+ This model is a fine-tuned version of [distil-small.en](https://huggingface.co/distil-small.en) on the librispeech dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2318
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+ - Wer: 4.4905
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-07
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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: 2
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+ - total_train_batch_size: 16
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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: 300
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+ - training_steps: 1000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:------:|:----:|:---------------:|:------:|
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+ | 0.651 | 0.5556 | 100 | 0.9641 | 3.4754 |
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+ | 0.5006 | 1.1111 | 200 | 0.7651 | 3.5039 |
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+ | 0.3531 | 1.6667 | 300 | 0.5188 | 3.5121 |
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+ | 0.2176 | 2.2222 | 400 | 0.3514 | 4.0258 |
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+ | 0.1834 | 2.7778 | 500 | 0.2878 | 4.3132 |
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+ | 0.1587 | 3.3333 | 600 | 0.2589 | 4.4049 |
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+ | 0.1553 | 3.8889 | 700 | 0.2447 | 4.5007 |
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+ | 0.1566 | 4.4444 | 800 | 0.2370 | 4.5007 |
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+ | 0.1226 | 5.0 | 900 | 0.2332 | 4.5048 |
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+ | 0.1533 | 5.5556 | 1000 | 0.2318 | 4.4905 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.0.dev0
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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