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  1. README.md +81 -0
  2. added_tokens.json +4 -0
  3. all_results.json +20 -0
  4. checkpoint-11000/added_tokens.json +4 -0
  5. checkpoint-11000/config.json +117 -0
  6. checkpoint-11000/optimizer.pt +3 -0
  7. checkpoint-11000/preprocessor_config.json +10 -0
  8. checkpoint-11000/pytorch_model.bin +3 -0
  9. checkpoint-11000/rng_state_0.pth +3 -0
  10. checkpoint-11000/rng_state_1.pth +3 -0
  11. checkpoint-11000/rng_state_2.pth +3 -0
  12. checkpoint-11000/rng_state_3.pth +3 -0
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  15. checkpoint-11000/tokenizer_config.json +51 -0
  16. checkpoint-11000/trainer_state.json +316 -0
  17. checkpoint-11000/training_args.bin +3 -0
  18. checkpoint-11000/vocab.json +2306 -0
  19. checkpoint-16000/added_tokens.json +4 -0
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  30. checkpoint-16000/tokenizer_config.json +51 -0
  31. checkpoint-16000/trainer_state.json +451 -0
  32. checkpoint-16000/training_args.bin +3 -0
  33. checkpoint-16000/vocab.json +2306 -0
  34. config.json +117 -0
  35. eval_results.json +9 -0
  36. predict_results.json +8 -0
  37. preprocessor_config.json +10 -0
  38. pytorch_model.bin +3 -0
  39. special_tokens_map.json +30 -0
  40. tokenizer_config.json +51 -0
  41. train_results.json +8 -0
  42. trainer_state.json +460 -0
  43. training_args.bin +3 -0
  44. vocab.json +2306 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-large-xlsr-53
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+ tags:
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+ - automatic-speech-recognition
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+ - ./sample_speech.py
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+ - generated_from_trainer
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+ model-index:
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+ - name: jako-xlsr
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+ results: []
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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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+ # jako-xlsr
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9486
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+ - Cer: 0.2606
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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: 0.0003
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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+ - total_eval_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_ratio: 0.03
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+ - num_epochs: 30
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Cer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 3.5667 | 1.14 | 1000 | 2.2323 | 0.5188 |
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+ | 1.5569 | 2.28 | 2000 | 1.3106 | 0.3527 |
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+ | 1.2238 | 3.43 | 3000 | 1.1109 | 0.3099 |
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+ | 1.0593 | 4.57 | 4000 | 1.0390 | 0.2891 |
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+ | 0.9658 | 5.71 | 5000 | 0.9731 | 0.2918 |
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+ | 0.8796 | 6.85 | 6000 | 0.9479 | 0.2696 |
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+ | 0.8022 | 8.0 | 7000 | 0.9331 | 0.2710 |
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+ | 0.7392 | 9.14 | 8000 | 0.9252 | 0.2746 |
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+ | 0.6694 | 10.28 | 9000 | 0.9318 | 0.2590 |
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+ | 0.5977 | 11.42 | 10000 | 0.9349 | 0.2674 |
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+ | 0.5484 | 12.56 | 11000 | 0.9409 | 0.2555 |
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+ | 0.5154 | 13.71 | 12000 | 0.9510 | 0.2719 |
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+ | 0.4767 | 14.85 | 13000 | 0.9556 | 0.2624 |
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+ | 0.4536 | 15.99 | 14000 | 0.9850 | 0.2684 |
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+ | 0.4195 | 17.13 | 15000 | 0.9894 | 0.2590 |
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+ | 0.3937 | 18.28 | 16000 | 1.0197 | 0.2698 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.1
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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+ "predict_steps_per_second": 0.651,
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+ "train_samples_per_second": 43.283,
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+ "train_steps_per_second": 1.352
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+ }
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